Top Data Engineer Jobs

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.

Senior Staff Data Engineer designs, builds, and owns cloud-based ETL/ELT pipelines and data products for Sales and Underwriting. Responsibilities include solution architecture input, CI/CD implementation, data quality and replication, hybrid cloud integration (AWS/Azure), mentoring, and evaluating new data technologies to support analytics and operational decision-making.

Lead a team building and operating large-scale, reliable data pipelines and warehouses. Mentor engineers, partner cross-functionally, manage SLAs, embed AI/LLM-driven Data Ops, and drive end-to-end delivery of canonical datasets and data infrastructure.

Design, build, and maintain cloud-native data processing architectures and pipelines (batch and near-real-time). Modernize on-premise SQL systems to Databricks/Azure, ingest and transform structured/unstructured data, monitor production data flows, troubleshoot performance and data quality, and collaborate with cross-functional and offshore teams to meet analytics and reporting requirements.

Lead data architecture and hands-on engineering to build a cloud data warehouse on Snowflake using Data Vault 2.0 and dbt. Design standards, implement ETL/ELT pipelines with Python and SQL, ensure data quality and governance, mentor engineers, and support on-prem to cloud migration.

Design, build, and maintain Snowflake-centered data warehouse and scalable ETL/ELT pipelines using IaC and orchestration tools; optimize performance, ensure data quality/security, support analytics and ML, and collaborate with cross-functional teams.

Lead design and build scalable data pipelines, data models, and ETL/ELT workflows. Mentor data engineers, set coding standards, improve data architecture and tooling, partner with Product and Platform teams, and deliver monitoring, data quality, and automation to support Data Operations.

Design, build, and maintain ETL/middleware pipelines to transform legacy HR data into Oracle Fusion HCM HDL/HSDL formats. Implement data cleansing, reconciliation, error handling, batch processing, and dashboards for large-scale federal agency migrations. Collaborate with legacy system teams, support mock migrations and cutovers, document designs and runbooks, and follow Agile/SAFe practices.

Remote entry-level Big Data Engineer role building data acquisition and munging pipelines. Requires strong Python3 (NumPy, Pandas), advanced SQL, scalable algorithm and data-structure implementation on distributed clusters, converting code to functional paradigms, and the ability to learn PySpark or Kafka quickly. Product-development, startup experience and real-world pipeline projects preferred.

Build and document DBT models in Snowflake, develop and maintain Tableau dashboards, handle data operations and troubleshooting, modernize data infrastructure, and own stakeholder relationships and requirements.

Support design, implementation, and maintenance of data integration and ETL processes. Perform basic data validation, database monitoring, scripting for transformations, document data mappings, and work with cross-functional teams under senior guidance to ensure data quality, security, and reliable data flows.

Designs and implements scalable real-time and batch data pipelines, optimizes performance and reliability, applies ML libraries and quantitative methods, builds cloud-native AWS data platform components, develops CI/CD and orchestration, performs testing/validation and documentation, and collaborates on data-centric initiatives in a financial services environment.

Build, maintain, and optimize cloud data pipelines and dbt models; design Airflow DAGs; implement dimensional models and BI dashboards; integrate healthcare data with HIPAA-compliant practices; contribute to RAG pipelines and MLOps workflows; review contractor code, monitor data quality, and document designs following governance standards.

Lead architecture and delivery of Boulevard's data platform, building foundational data models, pipelines, and customer-facing analytics. Collaborate with Product and Engineering to create scalable data products, Snowflake data sharing solutions, performant visualizations, and machine learning features (recommendations, forecasting, anomaly detection) to drive data-driven decision-making and product value.

Design, build, migrate, and maintain scalable data pipelines and architectures on Azure and Microsoft Fabric. Implement ETL/data integration, semantic models for analytics, CI/CD, monitoring, security controls, cost optimization, and testing. Collaborate with cross-functional teams and clients to translate business requirements into reliable, compliant data solutions.

Build and operate the data platform powering Vantaca IQ: ingestion and CDC pipelines, data modeling, aggregations and materializations, multi-tenant isolation, query/metrics APIs and reporting surfaces, LLM grounding/eval harnesses, and governed semantic layers to serve humans and agents with trustworthy intelligence.

The Senior Data Engineer will design and maintain data pipelines, ensuring data reliability and consistent models, while collaborating with stakeholders to improve data practices.

The Senior Staff Data Engineer will lead and influence data technology strategy across teams, focusing on infrastructure for data ingestion, storage, and analytics. Responsibilities include project execution, providing technical guidance, and ensuring reliability, performance, and security of data systems.

The Data Platform Engineer will develop and maintain scalable data platforms, implement data integration solutions, and mentor teams on best practices and standards.

The Sr Data Engineer will design and implement data solutions for Disney+, manage data quality, and work with teams to define requirements for new data features.

The Senior Data Engineer will build and manage data pipelines, optimize data structures, automate workflows, and collaborate with teams to ensure data reliability.

As a Senior Data Engineer, you will build and optimize foundational datasets, data pipelines, and analytical dashboards while ensuring data quality management.