Allata

Data Engineer

• Contribute to transformative enterprise data platform projects focused on developing data pipelines and logic engines to manage ingest, staging, and multi-tier data product modeling.
• Data enrichment using various OEM-specific data warehouse and data lake house platform implementations.
• Full life cycle design, build, deployment and optimization data products for multiple large enterprise industry vertical-specific implementations by processing datasets through a defined series of logically conformed layers, models, and views.

Data Engineer, Databricks

SDET

• Design, develop, and maintain automated test frameworks and select appropriate testing tools.
• Execute and maintain automated and manual test suites, create test cases, and report defects.
• Lead testing initiatives, define test strategies, and promote best practices within the team.
• Work closely with developers and product owners, participate in code reviews, and support feature development.
• Implement CI testing, participate in agile ceremonies, and drive process improvements.

Software Engineer – Test

Backend Engineer

• Design and develop user-friendly interfaces for bulk data editing using React.
• Utilize Java and React to implement user-friendly web-based UIs for importing and managing data at scale.
• Collaborate closely with stakeholders to understand requirements and deliver high-quality solutions.

FullStack Developer, Java, React

Full-stack Engineer

• Collaborate closely with the client to understand project requirements, manage expectations, and ensure clear communication on progress and deliverables.
• Identify, address, and resolve technical debt within the client’s existing tools, promoting sustainable and efficient solutions.
• Optimize and enhance file processing systems, focusing on scalability, reliability, and performance.
• Provide regular updates to internal and external stakeholders, ensuring project milestones and timelines are met.
• Contribute to a collaborative and efficient work environment, sharing best practices and fostering continuous improvement.

FullStack Developer, Node, Js

• Design and implement solutions using .NET and Angular.
• Work on the evolution of existing platforms.
• Implement and help to optimize new and existing applications.

FullStack Lead – .NET, Angular

• Design, develop, test, and deploy scalable and efficient software solutions to meet business and client requirements.
• Collaborate with cross-functional teams, including product managers, designers, and other engineers, to deliver high-quality software.
• Write clean, maintainable, and well-documented code following industry best practices.
• Debug and resolve software defects, ensuring optimal performance and reliability.
• Actively participate in Agile ceremonies, such as sprint planning, stand-ups, and retrospectives.

FullStack Developer – .Net, React

Business Analyst

• Collaborate with stakeholders to gather, prioritize, and document business requirements.
• Translate complex business needs into clear, actionable user stories and specifications.
• Conduct business process modeling, create process flow diagrams, and generate applicable scenarios for technical functionalities.
• Assess change proposals and define solutions to help the organization achieve its goals.
• Work closely with development teams to ensure proper understanding and implementation of requirements.
• Facilitate communication between technical teams and business stakeholders to ensure alignment and buy-in.
• Identify opportunities for process improvements and recommend innovative solutions.
• Support Agile ceremonies, such as sprint planning, backlog grooming, and retrospectives.

• Define the overall data platform architecture (Lakehouse/EDW), including reference patterns (Medallion, Lambda, Kappa), technology selection, and integration blueprint.
• Design conceptual, logical, and physical data models to support multi-tenant and vertical-specific data products; standardize logical layers (ingest/raw, staged/curated, serving).
• Establish data governance, metadata, cataloging (e.g., Unity Catalog), lineage, data contracts, and classification practices to support analytics and ML use cases.
• Define security and compliance controls: access management (RBAC/IAM), data masking, encryption (in transit/at rest), network segmentation, and audit policies.
• Architect scalability, high availability, disaster recovery (RPO/RTO), and capacity & cost management strategies for cloud and hybrid deployments.
• Lead selection and integration of platform components (Databricks, Delta Lake, Delta Live Tables, Fivetran, Azure Data Factory / Data Fabric, orchestration, monitoring/observability).
• Design and enforce CI/CD patterns for data artifacts (notebooks, packages, infra-as-code), including testing, automated deployments and rollback strategies.
• Define ingestion patterns (batch & streaming), file compacting/compaction strategies, partitioning schemes, and storage layout to optimize IO and costs.
• Specify observability practices: metrics, SLAs, health dashboards, structured logging, tracing, and alerting for pipelines and jobs.
• Act as technical authority and mentor for Data Engineering teams; perform architecture and code reviews for critical components.
• Collaborate with stakeholders (Data Product Owners, Security, Infrastructure, BI, ML) to translate business requirements into technical solutions and roadmap.
• Design, develop, test, and deploy processing modules using Spark (PySpark/Scala), Spark SQL, and database stored procedures where applicable.
• Build and optimize data pipelines on Databricks and complementary engines (SQL Server, Azure SQL, AWS RDS/Aurora, PostgreSQL, Oracle).
• Implement DevOps practices: infra-as-code, CI/CD pipelines (ingestion, transformation, tests, deployment), automated testing and version control.
• Troubleshoot and resolve complex data quality, performance, and availability issues; recommend and implement continuous improvements.

Data Architect – Databricks

Engineer

• Build and maintain IDP pipelines leveraging AWS services (Textract, Bedrock, Step Functions, Lambda, S3, DynamoDB).
• Leverage Amazon Bedrock Data Automation to support dynamic extraction logic and structured data generation.
• Develop prompt templates and Bedrock agents for entity recognition, summarization, and structured output generation.
• Automate document classification, metadata extraction, and validation flows using Bedrock model orchestration.
• Manage infrastructure and deployment using AWS CDK (TypeScript).
• Contribute to data automation frameworks for retraining, evaluation, and continuous improvement.
• Integrate with external APIs or data stores for downstream system ingestion.

AWS Cloud-Native Engineer – Intelligent Document Processing, Data Extraction

AI Engineer

• Architect and implement serverless AI workflows leveraging AWS Lambda, Step Functions, and Bedrock APIs.
• Design prompt and context engineering pipelines to generate recommendations dynamically from partial or tentative form responses.
• Implement data ingestion, validation, and contextual augmentation using AWS services (S3, DynamoDB, API Gateway, Lambda, Step Functions, EventBridge, etc.).
• Develop and deploy infrastructure as code using AWS CDK (TypeScript).
• Integrate LLM-based inference into end-user apps and internal tools.
• Optimize inference cost and latency through intelligent caching, grounding, and response evaluation mechanisms.
• Collaborate with UX and product teams to embed generative capabilities seamlessly into existing workflows.

AWS Cloud – Native AI Engineer

• Drive the end-to-end development of AI proof-of-concept solutions, collaborating with team members to create functional prototypes using AWS cloud services and AI tools.
• Partner directly with business stakeholders to understand processes, pain points, and workflow challenges, ensuring solutions are aligned with business needs.
• Design scalable, robust technical solutions utilizing AWS services (e.g., SageMaker, Bedrock, Lambda) and modern AI tools, ensuring alignment with business objectives and technical requirements.
• Convert business requirements into clear technical specifications and actionable plans for POC implementation, ensuring feasibility and alignment with business goals.
• Present findings, insights, and recommendations to senior leadership, translating complex technical concepts into clear business terms to facilitate decision-making.
• Serve as a subject matter expert in AI and AWS, identifying opportunities for process optimization and recommending innovative technologies to keep Allata at the forefront of the industry.

Lead Cloud-Native AI Engineer

QA Engineer

• Define the QA strategy and own a living QA test plan aligned to the product roadmap.
• Develop and maintain a regression test plan and ensure consistent execution each release.
• Document clear, traceable test cases and keep test assets up to date as features evolve.
• Organize and schedule QA activities; leverage internal manual testing resources effectively.
• Perform manual testing for new features, regressions, and production validation when needed.
• Monitor Jira boards and transitions to plan, prioritize, and track QA work.
• Update, triage, and reassign Jira tickets; maintain high-quality bug reports and traceability.
• Establish quality gates and lead QA signoff before merging the QA branch into production.
• Build and maintain automated tests for UI, API, and data validations; increase coverage over time.
• Integrate automated tests into CI/CD pipelines and enable reporting on quality status.
• Collaborate daily with product, engineering, and US-based stakeholders on scope, design, and release criteria.
• Define and track QA metrics (e.g., defect leakage, pass rates, automation coverage) and drive continuous improvement.
• Contribute to test data management, including synthetic data for data-centric validations.
• Champion risk-based testing, release readiness reviews, and post-release retrospectives.

QA Lead

Director

• Join us as a Director of Data & Insights to be a pivotal member of our executive leadership team, driving large-scale digital transformation initiatives with a commitment to quality and client satisfaction.
• In this role, you will design and implement innovative data solutions to empower our clients’ businesses, aligning data strategies with their objectives.
• Your strategic vision will steer the development of our people and service lines, fostering a collaborative culture that prioritizes team well-being.

Data Director

Product Manager

• Collaborate closely with business stakeholders, IT leaders, developers, and product designers to establish the vision, strategy, and roadmap for digital products, especially those that are AI oriented.
• Build and steward the development backlog.
• Turn qualitative and quantitative insights into valuable solutions and roadmaps that excel in both form and function.
• Conceive, communicate, and execute a creative vision in a strategic environment.
• Encompass product management through product ownership disciplines.

Digital Product Manager

Analyst

• Drive the shaping and application of analytical methods and frameworks in the conduct of strategic assessments, recommendations, and roadmaps in a collaborative fashion with your team and client. Take responsibility to proactively drive towards defined goals. Collect, synthesize, and interpret information in order to contribute to the recommendation of a path forward for our clients.
• Shape and develop outputs that convey a clear understanding of desired outcomes, current state operations and pain points, strategic context and value drivers, key imperatives and issues, options, prioritization criteria, strategic plans and roadmaps, and a relevant business case.
• Seek to understand, represent, and respond to the customer/user voice in all strategy and solutioning, subject to reasonable economics and market realities.
• Act as a high value contributor to Allata and joint Allata-Client teams, supporting alignment between strategy and/or solution development and the client’s broader business strategy.
• Contribute to the design and facilitation of workshops and working sessions to align cross-functional teams and stakeholders.
• Develop and deliver work-products and final deliverables with tight and compelling storylines supported by relevant and thoughtful analysis.

Strategy Analyst

Data Scientist

• Define and evolve Snowflake platform architecture, standards, and best practices.
• Translate business goals into a pragmatic technical roadmap and delivery plan.
• Lead and mentor data engineers; establish quality bars, review code, and guide execution.
• Manage delivery using Agile rituals; align priorities across data, analytics/BI, and application teams.
• Design, build, and optimize ELT pipelines on Snowflake with an ELT-first approach (dbt preferred).
• Implement modern data ingestion using tools such as Fivetran, ADF, Glue, or Matillion.
• Set up orchestration and CI/CD for data using Airflow or Dagster and Git-based pipelines.
• Ensure data quality, observability, monitoring, alerting, documentation, and runbooks.
• Apply performance tuning and cost optimization in Snowflake, including query profiling and warehouse sizing.
• Implement security and governance in Snowflake (RBAC, masking, row access policies, auditing, data sharing).
• Facilitate discovery with stakeholders, clarify requirements, and communicate trade-offs and recommendations.

Data Manager, Snowflake

• Architect, develop, and maintain scalable, efficient, and fault-tolerant data pipelines using Python and PySpark.
• Design pipeline workflows for batch and real-time data processing using orchestration tools like Apache Airflow or Azure Data Factory.
• Implement automated data ingestion frameworks to extract data from structured, semi-structured, and unstructured sources such as APIs, FTP, and data streams.
• Architect and optimize scalable Data Warehouse and Data Lake solutions using Snowflake, Azure Data Lake, or AWS S3.
• Implement partitioning, bucketing, and indexing strategies for efficient querying and data storage management.
• Develop ETL/ELT pipelines using tools like Azure Data Factory or Snowflake to handle complex data transformations and business logic.
• Integrate DBT to automate data transformations, ensuring modularity and testability.
• Ensure pipelines are optimized for cost-efficiency and high performance.
• Write, optimize, and troubleshoot complex SQL queries for data manipulation, aggregation, and reporting.
• Design and implement dimensional and normalized data models (star and snowflake schemas) for analytics use cases.
• Deploy and manage data workflows on cloud platforms using services like AWS Glue, Azure Synapse Analytics, or Databricks.
• Monitor resource usage and costs, implementing cost-saving measures such as data lifecycle management and auto-scaling.
• Implement data quality frameworks to validate, clean, and enrich datasets.
• Build self-healing mechanisms to minimize downtime and ensure reliability of critical pipelines.
• Optimize Spark workflows by tuning executor memory and partitioning.
• Conduct profiling and debugging of data workflows to identify and resolve bottlenecks.
• Collaborate with data analysts, scientists, and stakeholders to define requirements and deliver usable datasets.
• Maintain clear documentation for pipelines, workflows, and architectural decisions.
• Conduct code reviews to ensure best practices in coding and performance optimization.

Senior Data Engineer, Snowflake

• Architect, develop, and maintain scalable, efficient, and fault-tolerant data pipelines using Python and PySpark.
• Design and implement modern Data Warehouse and Data Lake solutions on cloud platforms (Azure or AWS).
• Build and automate ETL/ELT workflows using Snowflake, Azure Data Factory, or similar platforms.
• Leverage DBT to define, document, and execute data transformation and modeling workflows.
• Write optimized SQL queries for data retrieval, aggregation, and transformation to support analytics.
• Design pipeline workflows for batch and real-time data processing using orchestration tools like Apache Airflow or Azure Data Factory.
• Implement automated data ingestion frameworks for structured, semi-structured, and unstructured sources (APIs, FTP, data streams).
• Architect and optimize scalable Data Warehouse and Data Lake solutions using Snowflake, Azure Data Lake, or AWS S3.
• Implement partitioning, bucketing, and indexing strategies for efficient querying and storage management.
• Develop ETL/ELT pipelines to handle complex transformations and business logic; integrate DBT for modularity and testability.
• Ensure pipelines are cost-efficient and high-performance, leveraging pushdown optimization and parallel processing.
• Implement data quality frameworks to validate, clean, and enrich datasets and build self-healing mechanisms for reliability.
• Optimize distributed processing workflows for Spark by tuning executor memory and partitioning; profile and debug workflows.
• Deploy and manage data workflows on cloud services (AWS Glue, Azure Synapse, Databricks) and monitor resource usage and costs.
• Collaborate with data analysts, scientists, and stakeholders; maintain documentation and conduct code reviews.

Data Engineer, Snowflake

• Collaborate in defining the overall architecture of the solution, with experience in designing, building, and maintaining reusable data products using Data Bricks, Delta Live Tables (DLT), Pyspark, and SQL. Migration of existing data pipelines to modern frameworks and ensure scalability and efficiency.
• Develop the data infrastructure, pipeline architecture, and integration solutions while actively contributing to hands-on implementation.
• Build and maintain scalable, efficient data processing pipelines and solutions for data-driven applications.
• Monitor and ensure adherence to data security, privacy regulations, and compliance standards.
• Troubleshoot and resolve complex data-related challenges and incidents in a timely manner.
• Stay at the forefront of emerging trends and technologies in data engineering and advocate for their integration when relevant.

Senior Data Engineer, Data Bricks

• Design, implement, and optimize scalable Snowflake data solutions. Contribute to the overall data architecture and strategy. Collaborate with cross-functional stakeholders to gather data requirements and translate them into effective solutions. Develop efficient ETL/ELT pipelines to support analytics and data-driven applications. Ensure data accuracy, consistency, security, and performance across the Snowflake environment. Maintain comprehensive documentation for data processes, architecture, and best practices. Work closely with DevOps teams to implement CI/CD pipelines for data workflows.

• Design and develop user-friendly interfaces for bulk data editing using Angular.
• Utilize Java and Angular to implement web-based UIs for importing and managing data at scale.
• Modernize legacy processes and build scalable, maintainable solutions for healthcare partner organizations.
• Adopt pair programming and collaborative development practices to ensure high-quality code and knowledge sharing.
• Work guided by agile principles and collaborate closely with stakeholders and cross-functional teams to deliver measurable results.

Full Stack Developer, Java and Angular

• Allata is a global consulting and technology services firm helping organizations accelerate growth, drive innovation, and solve complex challenges.
• Architect and modernize secure, scalable solutions using cloud platforms and engineering best practices.
• Empower clients to unlock data value through analytics, visualization, and AI-driven automation.
• Develop client testing across manual, automated, and data testing efforts.
• Define and execute test strategies, plans, and CI/CD integration.
• Design and validate data testing using synthetic datasets.
• Collaborate with product, engineering, and US stakeholders to ensure quality across releases.
• Track quality metrics, report risks, and drive continuous improvement.

Allata is a global consulting and technology services firm with offices in the US, India, and Argentina. We help organizations accelerate growth, drive innovation, and solve complex challenges by combining strategy, design, and advanced technology. Our expertise covers defining business vision, optimizing processes, and creating engaging digital experiences. We architect and modernize secure, scalable solutions using cloud platforms and top engineering practices. Allata also empowers clients to unlock data value through analytics and visualization and leverages artificial intelligence to automate processes and enhance decision-making. Our agile, cross-functional teams work closely with clients, either integrating with their teams or providing independent guidance—to deliver measurable results and build lasting partnerships. We are seeking a skilled Lead Data Engineer Databricks to contribute to transformative enterprise data platform projects focused on developing data pipelines and logic engines to manage ingest, staging, and multi-tier data product modeling. Additionally, this includes but is not limited to data enrichment using various OEM-specific data warehouse and data lake house platform implementations for consumption via analytics clients. This role requires full life cycle design, build, deployment and optimization data products for multiple large enterprise industry vertical-specific implementations by processing datasets through a defined series of logically conformed layers, models, and views.