Top Data Engineer Jobs

Lead design and delivery of enterprise data platforms using Snowflake and AWS. Architect ELT/CDC pipelines, implement Data Vault 2.0 and dimensional models, optimize Snowflake performance, mentor engineers, partner with stakeholders, and ensure operational reliability and observability for analytics and BI workloads.

As a Senior Data Engineer, you'll define data ontology, collaborate with teams, design data pipelines, and optimize data infrastructures to support analytics for Yahoo Mail.

Design, ingest, validate, and manage complex financial and annuity data from external partners. Build and maintain ETL pipelines, SQL queries, and data quality controls; investigate data anomalies; collaborate with Accounting, Actuarial, and Technology; support reporting and process automation to improve financial and regulatory workflows.

Design, ingest, validate, and model complex financial and annuity data from external partners. Perform SQL-based ETL, data quality checks, root cause analysis, and collaborate with Accounting, Actuarial, and Technology to support reporting, valuations, and process automation.

Design and maintain a dbt-based business data layer for GTM metrics, centralize and reconcile multi-source data, implement automated data quality and reconciliation checks, align and document metrics with stakeholders, mentor analytics team, and lead root-cause investigations into complex data anomalies.

Design, build, and operate a privacy-safe, cloud-based data platform supporting batch and real-time pipelines, analytics, ML/AI, governance, observability, and high pipeline reliability. Partner with stakeholders, set data engineering standards, troubleshoot production incidents, and mentor engineers.

Lead design and implement scalable data infrastructure and transformations. Build data repositories, convert data science algorithms into robust pipelines, mentor a small data engineering team, ensure delivery quality, and collaborate with Product, Data Analysts, and Data Scientists.

Design and implement scalable data infrastructure and production data transformations. Lead and mentor a small Data Engineering team, ensure quality delivery, collaborate with Product, Data Analysts, and Data Scientists to operationalize algorithms and build robust data repositories.

The Data Engineer is responsible for developing data infrastructure, building data pipelines, managing data quality, and integrating analytics tools to support design and project operations.

The Founding Data Engineer will manage the company's data models, ensure metric integrity, and work with various teams to deliver reliable metrics and reporting systems.

The Data Engineer will structure and deliver translation memory data using a Translation Management System, requiring expertise in data science and cloud services.

The Data Engineer will construct data infrastructure, develop machine learning workflows, maintain data pipelines, integrate software components, and collaborate across teams to enable data-driven decisions.

Seeking an expert Data Engineer to construct data analytical infrastructure and pipelines, collaborating with Data Scientists to enhance machine learning workloads and automate data processes for national security missions.

As a Principal Data Engineer, you will design and implement data infrastructure and solutions, collaborating across teams to enhance healthcare data usage.

The Data Engineer I is responsible for building reliable ELT/ETL pipelines, implementing data quality checks, and optimizing data models using dbt, while collaborating with stakeholders to ensure data reliability and consistency.

The Data Engineer II will build and maintain data pipelines and infrastructure, ensuring data flow and integrity for investment decisions while collaborating with stakeholders.

Lead the design and migration of a data platform architecture. Manage data pipelines, mentor teams, and ensure platform reliability.

As a Data Engineer Lead, you will develop and maintain complex data applications, oversee data engineering activities, mentor teams, and work on mission-driven projects involving data insights.

As an FP&A Data Engineer, you will manage data pipelines, develop financial models, and automate reporting to assist management and teams in making data-driven decisions.

Designs, builds, and optimizes enterprise data pipelines, feature stores, and data warehouse infrastructure to support data science and production ML. Collaborates cross-functionally to deploy, monitor, and maintain scalable cloud and on-prem data systems, ensures data quality, and implements best practices for ETL, versioning, and ML model productionization.

Lead design, development, and optimization of ETL/ELT pipelines and data products for telematics and third-party data. Ingest large-scale datasets into the enterprise data lake/lakehouse, implement CI/CD and DataOps practices, orchestration (MWAA/Autosys/Control-M), observability, and resilient self-healing pipelines. Mentor team members, collaborate with architects, data scientists, and BI teams, run POCs, and apply RAG and AI-driven systems while ensuring governance, security, performance, and data quality.

Design, build, and maintain scalable semantic 360 data models and transformation pipelines. Implement cleansing, enrichment, business rules, KPIs, and scoring algorithms using SQL and Python/Scala. Employ AI coding assistants and modern AI engineering practices to accelerate development while ensuring traceability, data quality, performance, and alignment with product and analytics needs.

Lead Data Engineer/ETL role requiring 5-10 years of Informatica ETL experience. Responsibilities focus on BDM, TDM, data quality, big data, data warehousing, and star schema design. Strong verbal and written communication and a technical bachelor’s degree required. Unix experience is a plus.

Design, build, and optimize SQL Server-based data layers and Azure data solutions. Own query performance, indexing, concurrency, CDC pipelines, ORM data access patterns (C#), and database CI/CD. Partner with engineers and architects, mentor team members, and ensure scalable, low-latency data platforms.

Hands-on data and integration engineer responsible for building, supporting, and automating Canoe-related workflows and integrations. Develop and maintain data pipelines, SQL queries, validations, reconciliations, and monitoring to deliver alternative investment data to Snowflake, Addepar, reporting tools, and downstream systems. Troubleshoot data quality issues, support production feeds, manage exceptions, document mappings and runbooks, and collaborate with investment, reporting, technology, and vendor teams. Hybrid role requiring Baltimore office presence three days per week.