Top Data & Analytics Jobs

Support marketing analytics by analyzing digital channel performance, building and maintaining KPI dashboards, ensuring data accuracy, and collaborating with cross-functional teams to turn insights into actionable recommendations.

Design and build scalable data lakes, warehouses, and lakehouse architectures. Implement Python ETL/ELT pipelines, orchestrate workflows with Airflow, ingest data from third-party APIs, optimize columnar formats (Parquet/Avro/ORC), and work with Spark, Snowflake, and AWS/GCP to support ML and analytics. Act as technical consultant, ensure data integrity, and troubleshoot pipeline performance.

Design and build scalable data lakes, warehouses, and lakehouses. Implement Python ETL/ELT pipelines, orchestrate workflows with Airflow, ingest data from third-party APIs, optimize columnar formats, and work with Spark, Snowflake, and AWS. Act as technical consultant translating business goals into data architecture roadmaps.

Lead strategic analytics for marketing by building and deploying BI, predictive models, and reporting to influence senior leadership. Translate complex analyses into actionable recommendations, partner cross-functionally, identify market inefficiencies, advise on data acquisition, and support project delivery and stakeholder engagement.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Perform data extraction, cleaning, large-scale analysis, and visualizations to deliver HR insights. Build dashboards, write queries, document processes, communicate recommendations, and develop/test/deploy basic ML models using tools like Python, SQL, Alteryx, and Tableau.

Lead design and delivery of production data platforms, pipelines, and analytics. Architect Snowflake/Databricks solutions, build ETL/streaming ingestion, implement dbt transformations, data quality, observability, and governance, support BI and AI/ML feature/data pipelines, and mentor engineers while driving DataOps and platform best practices.

Design, develop, test and support Informatica ETL workflows integrating Oracle, MySQL, Salesforce and Data Lake sources. Create/modify Perl scripts, produce design documentation and data flow diagrams, collaborate with QA and business users, troubleshoot issues, and cross-train team members. Follow secure development practices and support performance and integration testing.

Design, build, and maintain large-scale GCP data pipelines and data warehouse solutions using Dataproc, GCS, BigQuery, Hadoop/Spark/Hive and Airflow. Mentor engineers, run agile ceremonies, prioritize backlog, provide on-call support, and deliver data models and products at multi-TB/PB scale.

Design, implement, and optimize scalable graph database solutions. Create graph data models, optimize queries and indexing for large datasets, integrate graph DBs with enterprise systems and ETL pipelines, recommend technologies, ensure security and availability, and collaborate with engineering and business teams on graph use cases.

Design, build, and operate a production data platform using Apache Iceberg and containerized data engines. Own CI/CD, automation, observability, incident response, security controls, and SLA monitoring for ETL/ELT and streaming pipelines; maintain catalogs and table health, run on-call rotations, and document practices.

Collect, analyze, and report on transportation claim data; monitor aging claims; produce daily/weekly/monthly reports; build and maintain ETL processes; use systems like NERP, SAP, WMP, TMS; meet management deadlines and support ad hoc reporting and special projects.

Own client-facing analytics and attribution: establish baselines, implement tracking and lead-to-sale matching, run holdout and lift experiments, quantify cost avoidance, build cross-client benchmarks, and translate findings into clear ROI narratives that inform pricing, product, and renewal conversations.

Lead enterprise data architecture strategy and design scalable, secure data solutions across cloud, AI/ML, automation, and data platforms for clinical trials. Establish standards, translate business requirements into architectures, mentor teams, enable AI-driven research, and influence the technology roadmap.