Top Data & Analytics Jobs

Lead architecture and evolution of enterprise-scale data platforms and pipelines for batch, real-time, and event-driven use cases. Drive data modeling, performance tuning, data quality, CI/CD, observability, incident response, and cross-team technical leadership. Mentor engineers, lead design reviews, and align data strategy across hybrid environments.

Own and scale streaming Kafka pipelines and large-scale Spark batch jobs processing billions of rows. Drive pipeline reliability, observability, data modeling, and cost/latency optimizations. Partner with data scientists and platform engineers, define SLOs, improve efficiency, contribute to shared infrastructure (Airflow, libraries, data catalog), and mentor junior engineers.

Design, build, and operate large-scale Hadoop-based data pipelines and streaming systems. Implement ETL/ELT, optimize Spark/MapReduce jobs, manage storage formats and governance, automate orchestration, monitor SLAs, collaborate with data scientists, document runbooks, and mentor junior engineers.

Lead design and delivery of scalable ETL/ELT pipelines into Snowflake, manage AWS data infrastructure, build Spark transformations in Databricks using Python/PySpark, and implement a semantic layer and modular dbt models for consistent, governed business metrics.

Design, build, and maintain Snowflake pipelines using Python and SQL to produce identity assets. Investigate record-level PII data quality, enhance AI-assisted and rule-based matching engines, build evaluation and monitoring tooling, collaborate with Data Science and Product, and support CI/CD, QA, and on-call responsibilities for production identity pipelines.

Design, build, and maintain scalable batch and streaming data pipelines and storage on AWS. Own features end-to-end, collaborate with cross-functional teams, ensure data quality and observability, mentor engineers, and occasionally support field deployments.

Design, develop, test, and maintain ETL solutions and data warehouse structures using SSIS and SQL Server. Build and support SSAS models, optimize ETL performance, ensure data quality, partner with stakeholders, and produce technical documentation to support BI and reporting initiatives.

Design, build, and maintain scalable ETL/ELT data pipelines and data platform architecture. Build programmatic pipelines (primarily Python), optimize analytical data models (SQL), integrate sources into Snowflake, use orchestration/transformation tools (dbt, Airflow, Dagster), improve data quality/observability, and partner with product, engineering, and analytics to deliver reliable data for decision-making.

Provide day-to-day administration and production support for Snowflake, Matillion, and related data platforms. Monitor jobs and performance, troubleshoot ETL/ELT and report refresh failures, manage access and deployments, maintain runbooks, and build AI-driven automation and agent-based workflows to improve operational reliability and efficiency.

Own and scale Provable's data platform on GCP: build and optimize ingestion pipelines from blockchain indexers, design privacy-aware data models, manage Postgres and BigQuery, develop high-performance data-serving APIs, ensure data quality and observability, and use IaC (Terraform, Helm) and Kubernetes to deploy and cost-optimize environments.

Design, build, and deploy analytics and ML solutions for learning data: ETL pipelines, data models, clustering/predictive models, and Power BI dashboards. Partner with faculty, provide training, and transfer analytics knowledge to staff.

Design, build, and operate large-scale Hadoop-based data pipelines and streaming solutions. Implement ETL/ELT with Spark, Hive, and Sqoop; optimize jobs for performance; manage storage on HDFS/Hive/HBase and lakehouse formats; automate orchestration with Airflow/Oozie; ensure data quality, governance, monitoring, and documentation; mentor engineers and lead architecture and performance reviews.

Design, build, and operate large-scale Hadoop-based data pipelines and streaming platforms. Implement ETL/ELT, optimize Spark/MapReduce jobs, manage storage formats and governance, automate orchestration, monitor production SLAs, and mentor engineers to deliver reliable analytics and ML-ready datasets.

Lead design and modernization of enterprise data pipelines across cloud and on-prem, define platform standards, mentor engineers, integrate utility systems (SAP, GIS, SCADA, AMI), ensure governed data for analytics and regulatory filings, and drive infrastructure-as-code, CI/CD, and observability for production pipelines.

The Senior Data Engineer will build scalable data pipelines, optimize Snowflake data warehouses, and enable reporting via Power BI while collaborating with stakeholders.

As a Senior Data Engineer, you'll design and implement ETL/ELT pipelines, write Python code for data processing, and optimize SQL models. You'll collaborate with teams and improve data architectures to support AI and marketplace strategies.

Design and manage a modular data layer architecture for scalable data ingestion and transformation. Develop ETL pipelines, implement metadata management, enforce data access policies, and report on performance and optimization.

The Senior Data Engineer designs, develops, and maintains ETL pipelines and database systems while ensuring data security and compliance with HIPAA. Responsibilities include SQL development, data integration, reporting, and collaborating with teams to support data needs.

Design and maintain data platforms for DHS, focusing on migrating from Elasticsearch to relational databases, optimizing performance, and ensuring data quality.

The Senior Data Engineer will design and implement data processing pipelines using Java and Spark, optimize performance, and mentor junior engineers while ensuring compliance with data governance standards.

The Staff Data Engineer will design and implement data architectures, manage partner integrations, build scalable data solutions, and mentor team members, ensuring efficient data operations and collaboration across teams.

Lead the design and implementation of scalable data architecture and engineering solutions, manage partner integration, mentor engineers, and ensure best practices in data systems.

The Senior Data Developer Tech Lead will design and manage scalable data solutions within Hadoop, lead streaming data architecture, optimize performance, and integrate AI/ML capabilities, while coaching team members and ensuring best practices in the banking domain.

Lead the design and implementation of Hadoop architecture and real-time data solutions. Coach team members, optimize performance, and ensure data governance within a small agile squad, focusing on AI/ML capabilities.

The Senior Data Engineer at BeyondTrust designs and manages data infrastructure, creates ETL pipelines, and optimizes database performance while ensuring data governance.