Top Data Engineer Jobs

Lead design, optimization, and management of enterprise data platform infrastructure with a focus on advanced SQL Server environments. Manage HA/DR, perform T-SQL development and performance tuning, enforce DB security, build scalable Python-based data pipelines and AWS IaC, integrate REST APIs, and architect AI/ML-ready data workflows.

Design, build, and maintain scalable data pipelines and dbt data models to support financial analytics. Integrate and transform complex financial datasets using SQL and Python, ensure data quality and compliance, deploy changes, and proactively monitor and improve ETL processes for reporting and strategic decision-making.

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.

The Data and Analytics Engineer will build and maintain scalable ELT pipelines, leveraging data for analytics and reporting within the Snowflake data architecture.

Data & Analytics Engineer at MojoTech, working with clients to define data requirements and deliver analytics solutions and pipelines. Requires 3+ years experience.

As a Senior Data Engineer, you will design and optimize data platforms, build data pipelines, mentor team members, and drive technical excellence while collaborating with cross-functional teams.

As a Staff Data Engineer, you will enhance and modernize data platform infrastructure, manage data processing platforms, and mentor junior engineers.

The Data & Analytics Engineer will model and serve data, improve architecture, and collaborate with teams to sustain the data strategy, requiring 5+ years of experience.

The Senior Data Engineer will manage and transform data pipelines, implement changes in Snowflake, monitor costs, and resolve data issues.

Lead data platform architecture and delivery for healthcare-focused Lakehouse/Warehouse solutions. Drive Databricks/AWS design, governance, security (PHI/PII), ETL/Delta Live Tables, APIs, modeling (FHIR/OMOP), IaC (Terraform), pipeline performance, and cross-functional collaboration to deliver scalable, production-grade data products.

Design and implement enterprise Databricks/AWS data platform and lakehouse solutions for healthcare data. Build and optimize ETL pipelines (Delta Live Tables), medallion architectures, streaming and batch processing, data models (FHIR/OMOP), governance (Unity Catalog), security for PHI/PII, IaC with Terraform, and collaborate with cross-functional teams to deliver reliable, cost-effective external and internal data products.

Design, build, and maintain scalable data pipelines into an enterprise cloud data warehouse to enable analytics, reporting, and advanced solutions. Collaborate with data architecture, IT operations, DBAs, infrastructure teams, analytics leaders, and business stakeholders to ensure system availability, performance, and timely resolution of data issues.

Design and build data infrastructure and data pipelines, focusing on big data processing, modeling, and automation to support engineering teams at NextSense.

The Principal Data Engineer leads the integration and optimization of data solutions, writes advanced SQL, automates processes using Python, and ensures data governance.

As a Senior Data Engineer, you'll optimize and maintain data platforms, develop integrations, and collaborate cross-functionally to enhance analytics and decision-making capabilities.

The Data Integration Engineer will design and build scalable data pipelines and manage data warehouses, integrating various data sources and ensuring data quality and operational reporting.

Nagarro seeks an Associate Principal Engineer in Big Data to leverage extensive IT experience for strategic organizational value. The role values self-starters and innovation.

As a Sr. Data Engineering Consultant, you will build and optimize scalable data solutions and mentor teams while collaborating with clients on data modernization projects.

Design, build, and operate high-scale streaming and batch data pipelines using Kafka, Flink, and Airflow. Optimize Redshift and Iceberg/Athena performance and cost. Ensure data quality, observability, SLAs, and serve reliable datasets/APIs. Mentor engineers and collaborate cross-functionally to deliver low-latency, production-grade telemetry and analytics data assets.

As a Lead Data Engineer, you'll optimize data workflows, manage data engineering projects, mentor junior engineers, and ensure robust data solutions meet business needs.

Lead design, build, and maintenance of scalable data pipelines and lakehouse infrastructure using PySpark, Databricks, and Airflow. Own data & ML platform (Terraform, Databricks), improve observability, data quality, and developer tooling, and partner closely with Data Science and engineering teams.

Design, build, and operate scalable batch and streaming data pipelines; partner with customer and product teams to implement health system integrations; improve monitoring, tooling, and data accessibility; serve as a dataset and tooling subject matter expert.

Lead end-to-end data and document migrations from legacy case management systems into Filevine. Assess source systems, design migration strategies, build and optimize SQL queries and ETL processes, perform data mapping, cleansing, validation, testing, and post-migration support. Document processes, contribute to tooling and best practices, and provide client training and troubleshooting.

Lead and mentor technical resolution of complex Data & AI production issues for customers, deep-dive into data pipelines and AI workflows, troubleshoot Spark/Delta/DLT/Model Serving, influence product improvements, and guide architects to build performant, reliable Databricks-based solutions.

Lead hands-on modernization of an enterprise data platform to an AWS lakehouse. Design, build, and operate production data pipelines using Python, PySpark, Spark (Glue/EMR), S3 Tables/Apache Iceberg, and orchestration (Airflow/Step Functions). Re-engineer legacy ETL, mentor engineers, perform code reviews, and partner with architects to deliver data products in an agile environment.