Top Data & Analytics Jobs

Design and build scalable platforms for data ingestion and storage, collaborate with hardware engineers, and define engineering processes at Sift.

Designs, builds, and supports data warehouse, BI and data visualization solutions. Gathers stakeholder requirements, develops ETL/transformation and integration services, ensures data design, transport, access, quality and metadata, and promotes best practices and standards across BI initiatives.

As a Senior Data Engineer, you'll transform raw data into datasets, design production pipelines, integrate customer data, and collaborate with various teams to ensure data quality and reliability.

The Senior Data Engineer will design and implement lakehouse architectures, optimize ClickHouse deployments, develop ETL/ELT pipelines, and create data models to support analytical and operational functions.

Design and build data pipelines and infrastructure; maintain data quality and accessibility; optimize data warehouse architecture while collaborating with teams to meet data needs.

As a Data & Automation Engineer, you'll build data platforms, design data models, manage datasets, and optimize data pipelines for analytics and decision-making.

Lead design and delivery of large-scale data pipelines and warehouse systems. Define technical strategy, enforce data governance, improve developer efficiency, mentor engineers, and align data engineering efforts with business goals to enable analytics and ML at scale.

As a Data Engineer, you'll build data infrastructure for analytics, drive business growth strategies, and enhance personalized user experiences at Eight Sleep.

Design and develop Big Data solutions using the Hadoop ecosystem (Pig, Hive, MapReduce, HBase, Spark, Kafka, Oozie). Implement Java-based services and scripting, tune performance for large datasets, participate in full project lifecycle, and collaborate with stakeholders. Role requires extensive travel and strong communication.

Develop and maintain Hadoop-based big data solutions using Pig, Hive, MapReduce, HDFS, HBase, Spark, Kafka and related tools. Implement web services/APIs, performance tune large datasets, script in Java and shells, participate in full project lifecycle, and collaborate with stakeholders. Extensive travel and on-site work required.

Design, build, and maintain data warehouses, data marts, and OLAP solutions; develop ETL frameworks, data models, SSIS/SSAS/SSRS artifacts, and performance-tuned SQL Server databases to support analytics and visualization projects.

Design and develop Big Data solutions using Hadoop ecosystem (Pig, Hive, MapReduce, HBase, YARN, Spark, Impala, Kafka, Oozie). Implement Java and scripting-based pipelines, tune performance on large datasets, participate across SDLC phases, troubleshoot, and collaborate with stakeholders in a global delivery environment.

Develop ETL and data visualization solutions for a big data customer and partner experience transformation program. Build native Hadoop and Vertica ETL pipelines, collaborate with stakeholders, and support data integration and visualization deliverables for analytics teams.

Design, build, maintain, and test big data solutions and preprocessing/reporting pipelines. Collect, parse, manage, analyze, and visualize large datasets. Test and deploy machine learning models for scoring and prediction. Collaborate in agile teams to deliver scalable, reusable code and production-ready analytics on cloud platforms.

Design, develop, maintain and test scalable big data solutions. Build preprocessing and reporting pipelines, collect/parse/analyze/visualize large datasets, test and deploy machine-learning models on big data, and work in agile teams to deliver analytics solutions.

Design, develop, test and maintain scalable big-data solutions and workflows. Collect, parse, analyze and visualize large datasets; evaluate, test and deploy machine-learning models for scoring and prediction. Work in an agile team, automate tasks using scripting, and leverage Hadoop/Spark and AWS for production pipelines.

Design, develop, and release data ingestion and streaming solutions using Big Data technologies (Flume, NiFi, Kafka, Spark/Storm). Collaborate with stakeholders and distributed teams, follow agile practices, and support data warehousing and reporting efforts.

The Senior Data Engineer designs and maintains data pipelines and architectures to support enterprise analytics, ensuring data quality and integration across systems.

Design, build and deliver SAP-originated and non‑SAP data in formats consumable by non‑SAP tools and external B2B partners using SAP BO/Data Services, BW/BI. Support ETL, integration and data delivery processes.

Seeking four DataStage ETL developers with 2-5 years experience for a long-term (2-3 year) contract. Candidates will be screened via phone or Skype; internal candidates preferred.

Map source data entities and create transformation rules for ETL developers to load into target systems. Work with business clients to interpret rules. SQL and Excel required; telecom billing system conversion/integration (Amdocs) is strongly preferred.

Design and build IBM DataStage ETL jobs to extract, transform, and load data into 3NF and star schemas. Implement Slowly Changing Dimensions and Change Data Capture, write strong Oracle SQL, use QualityStage and parallel processing, create source-to-target mappings, write/execute test cases, and use Unix shell scripting. Collaborate with stakeholders and maintain data warehouse ETL processes.

Lead design and build of a cloud-based big data analytics platform: implement analytics infrastructure, integrate streaming and batch data, develop distributed processing pipelines, manage predictive analytics models, and apply machine learning and Bayesian methods. Work involves Scala on OS X and AWS, Java and Clojure, Kafka/Samza, NoSQL, and following TDD, Agile, CI/CD practices.

Designs, builds, and supports secure data integrations, migrations, and ETL/ELT pipelines across ERP, student information systems, and the data warehouse. Works with stakeholders to gather requirements, automate data workflows, ensure data integrity, monitor integrations, document processes, and partner with security/privacy teams to maintain compliant data access. Supports system implementations and institutional reporting.

Lead design and scaling of enterprise data architecture and pipelines. Build and maintain ETL/ELT and CDC/streaming workflows, improve data quality and observability, own schema and warehouse modeling, implement governance (RBAC), and provide cross-functional technical leadership to enable trusted, scalable data for analytics and product teams.