Design and implement data integration and data warehouse solutions using big data technologies. Build cost-efficient, performant cloud data pipelines, apply data modeling and machine learning knowledge, and implement real-time streaming and aggregation patterns.
Role Big Data Engineer Responsibilities Implement Data integration and Data Warehouse based solutions using Big Data Technologies. Should be highly proficient in the use of Big Data / Open Source Technologies and standard techniques of Data Integration, Data Manipulation with hands-on contribution. Should be able to develop cost efficient and performant data pipelines in the cloud platform In-depth understanding of modern big data technology, including Data modeling and machine learning skills Knowledge of real time data streaming and aggregation architectural patterns and practice Essential Skills: 3+ Years hands on knowledge on SQL as well as SQL/NoSQL databases Proficient in programming languages such as Python and PySpark/Scala/Java
Similar Jobs
Automotive • Big Data • Insurance • Software • Transportation
Designs, builds, and maintains scalable ETL/ELT pipelines and finance data models using Snowflake, AWS, dbt Core, Python, and SQL. Develops Medallion architecture data marts, integrates ERP systems, and partners with stakeholders on financial workflows. Implements data governance, RBAC, automated quality testing, observability, documentation, CI/CD, and secure deployments. Monitors Snowflake costs and optimizes queries while supporting Oracle EBS integrations and the migration to Workday.
Top Skills:
AWSCi/CdDbt CoreGitOracle EbsPythonSnowflakeSQLWorkday
Information Technology • Consulting
Build and maintain ETL and data pipelines using Python, PySpark, and AWS services. Orchestrate workflows, develop event-driven integrations, optimize data storage and queries, process API and JSON data, and implement data quality monitoring. Support CI/CD, production operations, cloud migration, data lake and lakehouse initiatives, and near-real-time systems while collaborating with stakeholders to deliver technical solutions.
Top Skills:
Amazon AthenaAmazon CloudwatchAmazon DynamodbAmazon EmrAmazon KinesisAmazon RdsAmazon RedshiftAmazon S3Amazon SnsAmazon SqsApache AirflowAPIsAws GlueAws LambdaAws Step FunctionsCi/CdData LakesData WarehousingGithub CopilotGitlabJSONLakehouseMcpOraclePysparkPythonSQLTerraform
Social Media
Lead Pinterest’s technical strategy and roadmap for scalable big data and AI infrastructure. Build frameworks for compute, job, resource, scheduling, and shuffle management across petabyte-scale datasets. Partner with internal customers, provide company-wide technical leadership, and improve data processing reliability, speed, and efficiency.
Top Skills:
AWSFlinkGoJavaKubernetesPythonPyTorchRayScalaSparkTensorFlow
What you need to know about the Colorado Tech Scene
With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute


