Top Data Engineer Jobs

Build and maintain centralized pricing data infrastructure, scalable workflows, and data pipelines; integrate AI capabilities; deliver pricing tools, reporting, and governance to support data-driven pricing and budgeting across the firm.

Intern will explore and clean unfamiliar datasets, write code to ingest, transform, and monitor data quality using Python, SQL, and OCaml, work with structured and unstructured data, complete two owned projects, and be mentored by full-time Data Engineers.

The role involves building data pipelines, processing structured and unstructured data, and collaborating with a multidisciplinary team on technology solutions for clients in various sectors.

As a Data Engineer, you will design, build, and maintain scalable data platforms, working on mission-driven projects that analyze big data to derive insights. You will collaborate with multi-disciplinary teams in a fast-paced environment.

Build and scale core data infrastructure and foundational datasets. Design, develop, and maintain scalable data pipelines for analytics, ML, experimentation, and product use cases. Implement data quality, audits, alerting, and anomaly detection. Partner with product, engineering, and business stakeholders and help establish long-term, scalable data architecture and tooling.

Owner of marketing-focused data engineering: build and maintain integrations, tracking, and pipelines across BigQuery, ClickHouse, GCS, and external systems; troubleshoot tracking, payment, and data quality; collaborate with cross-functional teams and document data flows.

The Data Engineer will build and optimize data pipelines and infrastructure, ensuring data quality for analytics and machine learning initiatives while collaborating with teams to develop data solutions.

Lead design, implementation, automation, and maintenance of large-scale ETL pipelines and scalable data solutions. Optimize SQL and database performance, collaborate with analytics and business stakeholders to translate needs into data requirements, apply best practices (version control, code reviews, data validation), mentor junior engineers, and ensure delivery of accurate, robust data products while complying with internal policies and regulations.

The Senior Research Engineer will curate large datasets, automate data pipelines, optimize queries, and support data-driven research impacting business outcomes.

Own and evolve the data lake and analytics stack powering fleet observability. Build and maintain scalable ETL/ELT pipelines, operate data lake infrastructure (Iceberg, Trino, Airflow, Spark, Superset), produce analytics and executive reporting, create dashboards and runbooks, and implement data governance and observability.

As a Data Engineer at Booz Allen, you'll manage data engineering activities, develop scalable platforms, and work with multidisciplinary teams to extract meaningful insights from big data.

Design, build, and maintain scalable ETL/ELT pipelines and data platforms. Collaborate with cross-functional teams to ingest, parse, convert, and operate structured and unstructured data for analytics, reporting, and mission-driven use cases while ensuring platform scalability and monitoring.

Support the Data team by building and maintaining scalable ETL pipelines and data infrastructure for multi-modal medical datasets, automate data QA, optimize data delivery on cloud platforms, and provide analytics tools and secure cross-border data storage.

Design and implement end-to-end data integration and warehousing solutions for large volumes. Implement Hadoop/Hive data movement, script in Linux shell and Python, develop SQL for integration and analysis, and perform high-volume DW performance tuning. Vertica experience is a plus. Requires technical independence and a BS in CS/EE.

Design, architect and manage AWS Big Data solutions; build and tune Hadoop-based ETL/ELT pipelines; process unstructured and real-time data; develop with Java/Python/C++/scripting languages; collaborate on BI/visualization; ensure performance and robust workflows. 6-month contract, US work authorization required.

Design, implement, and optimize Snowflake data storage and ETL solutions. Write and tune SQL, integrate data sources and BI tools, ensure data security and compliance, and collaborate with teams to meet business objectives.

Develop and maintain Python-based data applications and pipelines: fetch data from databases/APIs/files, build Pandas DataFrames/NumPy arrays, write complex SQL and data transformations, handle nested JSON, and collaborate with data science teams to deliver production data platforms.

Build and implement a transactional data system: design and develop SSIS ETL packages, consume web services in ETL, create SSRS reports for ETL status, and implement T-SQL/SQL Server solutions per functional requirements and system design.

Design, build and maintain a data transactional system performing ETL and web service calls to synchronize state between systems. Develop SSIS packages, data models, dictionaries, test plans, and assist architects on database strategy.

Develop ETL, reporting, and OLAP solutions using SQL Server (SSIS, SSRS, SSAS) and T-SQL; perform impact analysis, document requirements, support ETL/data quality, and assist database architecture and defect resolution.

Implement OLTP and OLAP systems to persist court information from functional requirements and system design. Perform ETL, export data to external agencies, use managed service calls, design and model database structures, design/code/deploy SSIS packages, document data dictionaries and package definitions, develop SSIS test plans, and support architects.

Design, develop, and optimize Teradata data solutions: elicit requirements, create logical/physical designs, write SQL (views/procs/macros), use Teradata utilities for data loads, tune performance for large datasets, coordinate stakeholders, and write Unix shell scripts.

Elicit and analyze requirements; design logical/physical Teradata solutions; develop ETL using Teradata utilities; write SQL (views, stored procedures, macros, functions); perform performance tuning for large datasets; write Unix shell scripts; coordinate with stakeholders and support BI/DW initiatives.

Design, build, and maintain scalable ETL/ELT pipelines ingesting travel-related data from multiple sources. Integrate and model data in cloud warehouses (Snowflake/BigQuery/Redshift), implement data quality and monitoring, support real-time streaming, and ensure data governance and regulatory compliance. Collaborate with analysts, data scientists, and product teams to deliver reliable datasets for personalization, forecasting, and optimization.

Build and own customer data ingestion and large-scale pipelines powering AI workers. Design syncing, retrieval, and data lake systems, improve reliability/observability, partner with product/backend teams, and contribute across infrastructure to give AI agents access to enriched customer data.