Data Engineer

• Develop and maintain data pipelines, ETL processes, and workflows to collect, clean, and transform data from various sources into usable formats
• Ensure data integrity, quality, and accuracy throughout the data processing lifecycle
• Analyze and interpret health insurance exchange data and related datasets to identify patterns, trends, and insights
• Generate reports, dashboards, and visualizations to communicate findings effectively to non-technical stakeholders
• Design, develop, and maintain databases, data models, and schemas for efficient storage and retrieval of data
• Collaborate with cross-functional teams to understand business requirements and translate them into data solutions
• Stay up to date with emerging technologies, industry trends, and best practices in data analysis, engineering, and visualization
• Identify opportunities to improve data infrastructure, processes, and analytics capabilities

• 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

• 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

• You will work closely with finance, accounting, billing, and revenue teams to understand their main pain points and translate them into self-serve, reliable, and scalable data solutions
• You are expected to mentor other team members and be a champion of engineering excellence across the organization
• You will be part of a small team with a large amount of ownership and autonomy, managing initiatives directly from design through execution
• You will have the freedom to suggest and drive organization-wide initiatives that shape the financial data vision and roadmap
• You will own critical data integration pipelines and models, ensuring uniform, reliable, timely, and accurate financial reporting

Senior Data Engineer, Finance

• Drive the Data Architecture and Data platform modernization for the Workplace Investing division of Fidelity Investments
• Collaborate closely with business partners and technology teams to understand business objectives
• Define strategies to modernize legacy systems
• Leverage AI/ML-enabled approaches for mainframe modernization
• Design and lead proof-of-concepts that demonstrate AI value in platform modernization

Director, AI/ML, Data Architecture

• Develops and delivers data solutions to accomplish technology and business goals
• Works across development teams to contribute to data requirements
• Builds processes supporting data transformation, data structures, metadata, data quality controls, dependency

Data Engineer II – Credit Review Automation, Analytics

• Developing and delivering data solutions to accomplish technology and business goals
• Integrating, cleaning, transforming, and controlling data in operational and analytical data systems
• Working with stakeholders and Software Engineering teams to implement data requirements
• Analyzing performance and troubleshooting data problems
• Supporting Automation Team processes and tools

Data Engineer II – Automation Team

• Developing and delivering data solutions to accomplish technology and business goals and initiatives
• Performing code design and delivery tasks associated with data integration, cleaning, transformation, and control
• Working with stakeholders and Product and Software Engineering teams to implement data requirements
• Analyzing performance and troubleshooting data problems
• Supporting Automation Team to achieve effective coverage through analytics and automation

• 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

• Collaborate with data scientists and machine learning engineers to understand data requirements for LLM and machine learning model fine-tuning.
• Design, build, and maintain scalable data pipelines to ingest, process, and store massive and diverse healthcare datasets.
• Implement robust data validation and monitoring to ensure the integrity, accuracy, and consistency of all training datasets.
• Implement robust data cleaning, validation, and transformation processes to ensure data quality and integrity.
• Develop and optimize data structures and schemas for efficient access and utilization by LLMs and machine learning models.
• Work with the team to identify and acquire new data sources, ensuring compliance with relevant healthcare regulations (e.g., HIPAA).
• Monitor data pipeline performance, troubleshoot issues, and implement optimizations to improve efficiency and reliability.
• Document data engineering processes, data models, and data dictionaries.
• Stay up-to-date with the latest advancements in data engineering, big data technologies, and machine learning.

AI Data Engineer

• Design and build scalable Databricks data pipelines
• Develop ETL/ELT pipelines using PySpark
• Implement data ingestion and transformation frameworks
• Optimize Spark workloads for performance and scalability
• Establish engineering standards and mentor engineers
• Collaborate with architecture and analytics teams to enable data products

Lead Data Engineer – Databricks

• Build and maintain PySpark pipelines in Databricks
• Develop scalable data ingestion and transformation workflows
• Implement data validation and quality checks
• Optimize Spark workloads and processing performance
• Work closely with architecture and analytics teams

See all jobs on JobTailor

Data Engineer

Data Engineer

Staff Software Engineer, Data Platform

Senior Data Engineer, Finance

Director, AI/ML, Data Architecture

Data Engineer II – Credit Review Automation, Analytics

Data Engineer II – Automation Team

Data Engineer II – Automation Team

Data Architect – Data Ecosystems

AI Data Engineer

Lead Data Engineer – Databricks

Senior Data Engineer – PySpark