Data Engineer

• Develops, tests, and maintains complex prioritized engineering (design/build/test) work as a member of a data analytics product pipeline architecture and infrastructure team
• Investigates and analyzes feasibility of data integration prototypes and program requirements
• Develops specifications and plans the full range of programming actions to produce data integration components
• Develops and maintains complex automated ETL/ELT pipeline architecture that cleans, transforms, and aggregates data from disparate sources using architecturally approved tools, programming languages, and services to deliver a data mesh approach
• Develops and maintains complex automated ETL/ELT monitoring and alarming solutions using architecturally approved languages and services
• Monitors, troubleshoots, and optimizes data pipelines for quality, performance, and reliability creating a single source of truth providing business customers with highly reliable and quality data
• Builds complex unit tests to enable test driven development and automation to drive code reliability
• Develops, maintains, tests, and deploys code with architecturally approved toolsets using Dev Ops practices, ETL/ELT pipelines, data catalogs and data queries
• Maintains data solutions in a divest state to ensure business functionality until replaced with new technology
• Balances and designs data analytics product solutions based on cost and performance to meet data needs and business requirements
• Guides business customers to develop, troubleshoot, and optimize complex SQL and ETL/ELT solutions to solve reporting, metrics, and analytics problems
• Collaborates with cross-functional teams to understand data requirements for data analytics products and translate them into scalable and efficient data solutions

Data Engineer III

• Own day-to-day administration, configuration, and health of Oura's global Databricks environment, serving stakeholders across IT, business, and data science domains.
• Manage workspace governance: access controls, cluster policies, cost monitoring, job scheduling, and security configurations.
• Support onboarding of new teams and use cases onto the Databricks platform as Oura unifies data across Finance, SDM, Commerce, Marketing, and other domains.
• Proactively identify and resolve performance bottlenecks, reliability issues, and cost inefficiencies.
• Maintain SLAs for platform availability and incident response across global time zones.
• Partner with IT and Data Architecture teams to align platform configurations with Databricks best practices and Oura's Data Mesh approach.

Senior Data Engineer, Data Platform Admin

• Implement and optimize ETL process to ensure data accuracy, consistency, and scalability.
• Support the buildout, migration, and maintenance of the company’s Enterprise Data Lake house.
• Work with senior engineers to design and develop data pipelines that extract data from various sources, transform it into the desired format, and load it into the appropriate data storage systems.
• Work closely with Information Technology teams to implement continuous integration and deployment (Cl/CD) pipelines using Azure DevOps.
• Assist in administering and optimizing Azure Databricks clusters and ensure efficient data processing.
• Collaborate with analysts and business units to design and implement efficient data models.
• Determine data tracking and storage needs, perform data auditing and validation, perform data mapping, loading and conversion planning, and resolve data issues or discrepancies.

• Serves as a lead in the analysis of business requirements associated with the design and implementation of highly complex, highly scalable enterprise data processes
• Designs and develops robust and efficient processes for extracting, loading and transforming data to meet the needs of enterprise scale projects
• Provides guidance and participates in activities involved in the analysis, design, development, troubleshooting, debugging and maintenance of an enterprise data management and data ecosystem
• Identifies, investigates, tracks, and resolves the most complex technical errors ensuring the solution is timely and of acceptable quality
• Establishes and enforces database standards, guidelines, procedures and quality assurance for database deliverables such as conceptual design, logical data model capacity planning, external data interface specs, data loading, data maintenance plan and security
• Reviews and analyzes data objects and models to improve data management and data access
• Designs, constructs, tests and implements extraction and transformation programs, processes and cycles for historical and current source data
• Creates technical specification for supporting enterprise data transformation processes and supplementing system documentation for ETL processes
• Performs data profiling, source-target mappings, data transformation development, optimization, testing and implementation
• This position participates and serves as a lead in maintaining the ETL environment for the company’s system-wide enterprise data warehouse.

Supply Chain Data Engineer

• Design and develop data serving and semantic layers to support business needs
• Develop data models for use by analysts and applications using modern dimensional modeling practices
• Build and maintain robust, scalable data pipelines using ETL, ELT processes
• Create efficient and performant data models to support business requirements
• Implement and automate data quality checks and monitoring to ensure data accuracy
• Manage, troubleshoot and optimize existing data infrastructure, including cloud-based solutions
• Leverage cloud data platforms (Fabric, Databricks, Snowflake, etc.) for data storage, processing, and analysis
• Collaborate with data analysts, data scientists, and business stakeholders to understand their data needs

• Conduct requirements gathering with our clients to identify what data needs to be imported into AgencyBloc, including file attachments.
• In collaboration with the Implementation Manager, establish project timelines and tasks.
• Perform source system data analysis in order to develop source to AgencyBloc data mapping.
• Perform data cleaning, validation and reconciliation to ensure data accuracy and integrity.
• Conduct data migration and testing to ensure all client data is correctly mapped to their AgencyBloc account.
• In collaboration with the Implementation Manager, respond to client feedback, making any updates to the data mapping necessary.
• Develop and maintain process and source system documentation.
• Mentor and train team members, contractors, and clients as necessary.
• Direct and support data migration contractors as necessary.

Senior Data Migration Specialist

• Provide technical leadership to data engineers, setting standards for solution design, coding practices, data governance, and quality.
• Define and evolve the enterprise data architecture leveraging Snowflake, Data Vault 2.0, and modern event driven and ELT frameworks.
• Lead architecture reviews, establish engineering best practices, and guide platform modernization efforts.
• Mentor engineering team members, facilitate code reviews, and promote continuous learning and innovation.
• Architect and oversee the delivery of scalable data pipelines, ingestion frameworks, and transformation processes using Snowflake, Python, Spark, Informatica (PowerCenter/IDMC), AWS Glue, and cloud-native tooling.
• Design and maintain enterprise data models, including Data Vault 2.0 (Hubs, Links, Satellites, PIT, Bridge structures) and dimensional models.
• Develop and optimize Snowflake platform capabilities, including: Snowpipe, Streams, Tasks, File Formats, External Stages Dynamic Tables and ELT pipeline automation.
• Warehouse sizing, performance tuning, and cost optimization.
• Implement scalable batch, micro-batch, and real-time ingestion solutions following best practices.
• Translate complex business requirements into technical design specifications and actionable development plans.
• Partner with product owners, business stakeholders, architects, and analytics teams to deliver high-impact data solutions.
• Manage technical execution across multiple initiatives, ensuring alignment with enterprise priorities, data strategies, and delivery timelines.
• Oversee documentation, deployment readiness, testing processes, and quality assurance for production releases.
• Ensure operational reliability, data accuracy, and performance of enterprise data warehouse and analytical environments.
• Lead root-cause analysis for production issues and drive implementation of long-term preventative solutions.
• Conduct performance optimization on Snowflake workloads, SQL queries, pipelines, and integrations.

Senior Data Engineer

• Deploy new data pipelines
• Design & build data observability platforms and metrics
• Build metadata driven pipeline solutions
• Monitor and optimize data transformations
• Build third party data integrations

• Design, build, and maintain scalable Snowflake-based data warehouse architectures, ensuring performance, reliability, and extensibility for future growth.
• Own data architecture and technical design decisions, including data models, integration patterns, and optimization strategies.
• Transform raw source data from multiple internal and external systems into analytics-ready data models using industry best practices.
• Lead and contribute to warehouse development using dimensional modeling techniques (e.g., star schemas, slowly changing dimensions).
• Develop and manage data pipelines using Snowflake features such as Snowpipe, tasks, stored procedures, and performance optimization techniques.
• Manage and monitor data integrations with internal systems via APIs, application calls, or custom code to ensure data accuracy and reliability.
• Apply auditing, change tracking, error handling, and monitoring across large datasets to maintain high data quality standards.
• Identify and resolve data quality issues and implement controls to distinguish valid vs. invalid data used in decision-making.
• Leverage Python and application knowledge to interact with and extract data from other systems.
• Provide technical leadership through coaching and mentoring junior and mid-level data engineers, including code reviews, design feedback, and best-practice guidance.
• Contribute to and help define data engineering standards, best practices, and documentation across the team.
• Collaborate across teams to support day-to-day operational data needs and continuously improve data pipelines and processes.

• Meet with clients to understand their current business processes and needs to provide consulting services and direction on how to build or grow their current data strategy.
• Work with HBS Sales Solutions consultants to identify and grow opportunities within HBS client environments.
• Support and administer the underlining infrastructure and layout of a client data environment.
• Develop and design the process for the customer data collection process.
• Develop policies and procedures for the collection and analysis of data.
• Review customer sources to ensure integrity of the data collection process.
• Collaborate with the BI Data Developers to ensure the requirements are being met to build the right solution needed.
• Estimate development effort required to deliver data customer needs and requests.
• Use business analysis skillset to identify development needs for the purpose of streamlining and improving the operations of the organization for efficiency and profitability.
• Ability to work independently or as a team on project-based solutions for clients.
• Work with teammates to continue to grow and mature data services and delivery options for HBS clients.
• Based on experience, one may mentor other engineers in developing scalable, secure, high-performance BI and Data solutions.
• Meet annual billable hour goal, as defined by HBS. This number may change over time as the business evolves.

• Own End-to-End Delivery of Core Data Platform Components
• Design and ship the data normalization, schema mapping, validation, enrichment, and distribution pipeline for a net-new intelligent data warehouse
• Write production code as a hands-on individual contributor. This is not a role that delegates implementation to others
• Take technical ownership from architecture through deployment, with accountability for reliability, performance, and correctness
• Drive Technical Architecture
• Partner with a small seed team of senior engineers to define the end-to-end architecture for an AI-native data warehouse serving institutional financial clients
• Bring opinionated decisions on schema design, normalization strategies, API exposure patterns, and data distribution approaches
• Evaluate and select technologies with a bias toward what ships well and scales sustainably
• Build AI Evaluation Infrastructure
• Design and implement the evaluation framework that makes AI-generated outputs trustworthy in high-stakes financial data contexts
• Build cross-model comparison tooling, deterministic validation checks, and human-in-the-loop review workflows
• Contribute to shared AI infrastructure that will serve as a foundation for multiple products across the company
• Ship with AI-Native Development Practices
• Use agentic coding tools and LLM-assisted development as your primary workflow; this is how the entire team operates
• Bring strong opinions about how to get the most out of AI-assisted development while maintaining quality and reliability
• Contribute to the team’s evolving practices around AI-accelerated SDLC
• Establish Technical Standards
• As an early senior voice on a new team, set coding standards, review practices, and architectural documentation that will scale
• Help define what “good” looks like for a team building at speed without sacrificing quality
• Mentor and provide technical guidance as the team grows from seed squad to full delivery organization
• Collaborate Across Engineering and Product
• Work closely with your engineering manager, peer engineers, and product management to translate requirements into executable technical plans
• Participate actively in design reviews and roadmap discussions with grounded, implementation-level perspective
• Engage directly with the nuances of private markets data – fund administration, investment data schemas, institutional reporting workflows – to build domain intuition that improves your technical decisions

Staff Software Engineer, Data Platform

• Design the vision and blueprint of an organization’s data framework.
• Design and manage data systems, set policies for how data is stored and accessed, coordinate various data sources within an organization, and integrate new data technologies into existing IT infrastructures.
• Data modeling and design, including software development and database administration.

Data Architect – Data Ecosystems

• Work collaboratively with other engineers, data scientists, analytics teams, and business product owners in an agile environment.
• Support the operation of Cloud and On-Premises enterprise data infrastructure and tools.
• Assist in the design and support of data pipelines to automate the ingestion, processing, and delivery of structured and unstructured batch and real-time streaming data.
• Assist in the design and support of data APIs and data delivery services.
• Assist in testing and integration of data related tools, frameworks and applications as directed.

• Work collaboratively with other engineers, data scientists, analytics teams, and business product owners in an agile environment
• Architect, build, and support the operation of Cloud and On-Premises enterprise data infrastructure and tools
• Design robust, reusable and scalable data driven solutions and data pipeline frameworks to automate the ingestion, processing and delivery of both structured and unstructured batch and real-time streaming data
• Lead the development of data APIs and data delivery services to support critical operational processes, analytical models and machine learning applications
• Assist the selection and integration of data related tools, frameworks and applications required to expand platform capabilities
• Understand and implement best practices in management of enterprise data, including master data, reference data, metadata, data quality and lineage

See all jobs on JobTailor

Data Engineer III

Senior Data Engineer, Data Platform Admin

Data Engineer

Supply Chain Data Engineer

Data Engineer

Senior Data Migration Specialist

Senior Data Engineer

Data Engineer

Senior Data Engineer

Senior Data Engineer

Staff Software Engineer, Data Platform

Data Architect – Data Ecosystems

Data Engineer

Lead Data Engineer