科技職缺
職缺列表
Data Engineer - Senior 2
Senior data engineer at Cummins leading the design, development, and maintenance of a cloud-based data and analytics platform. Builds scalable data pipelines, data products, and AI/ML-ready datasets using Spark, Hadoop, SQL, Kafka, and modern ETL/ELT tools across Supply Chain, Finance, and Product domains.
Data Engineer - Senior 1
Senior Data Engineer at Cummins leading design and development of enterprise data pipelines and analytics platforms using Spark, Hadoop, Kafka, cloud data warehouses, and ETL/ELT tools, supporting analytics, AI/ML, and GenAI use cases across Supply Chain, Finance, and other domains.
Data Engineer 9
Data Engineer building and maintaining enterprise data pipelines, ETL/ELT transformations, and curated datasets across Supply Chain, Quality, Finance, and Product Lifecycle domains to power analytics, automation, and GenAI use cases using cloud big-data platforms.
Data Engineer 5
Data Engineer at Cummins building and maintaining enterprise-scale data pipelines, ETL/ELT transformations, and governed data products on cloud and Big Data platforms to support analytics, AI/ML, and GenAI use cases across Supply Chain, Quality, Finance, and Product Lifecycle domains.
Data Engineer 12
Data Engineer at Cummins building enterprise data products, pipelines, and curated datasets that support analytics, automation, and GenAI use cases across Supply Chain, Quality, Finance, and Product Lifecycle using Spark, Kafka, cloud platforms, SQL, and modern ETL/ELT tooling.
Data Engineer - Senior 6
Senior data engineer at Cummins designing and operating large-scale cloud data pipelines, data lakes, and ETL/ELT solutions using Spark, Scala/Java, Hive, HBase, Kafka, SQL, and NoSQL stores to deliver AI/ML- and analytics-ready data products across enterprise domains.
Data Engineer - Senior 4
Designs, builds, and optimizes reusable, governed enterprise data pipelines and cloud platforms for analytics, reporting, APIs, automation, and GenAI. The role spans SQL, Spark, Scala/Java, Kafka, Hadoop, ETL/ELT, data modeling, quality, lineage, and scalable data architecture.
Data Engineer 7
Cummins is hiring a Data Engineer in Pune to build and maintain enterprise data products—pipelines, transformations, and curated datasets—for Supply Chain, Quality, Finance, and GenAI use cases, using Spark, Scala/Java, Hadoop, Kafka, SQL, and cloud-based platforms in an Agile environment.
Data Engineer - Senior 3
Senior Data Engineer at Cummins leading design of cloud-based data and analytics platforms. Builds scalable ETL/ELT pipelines, data lakes, and AI-ready data products for analytics, reporting, and GenAI use cases using Spark, Scala/Java, Kafka, Hadoop ecosystem, and SQL.
Data Engineer
Build and maintain data pipelines, debug production data platform issues, design data models and schemas, and optimize data collection, storage, access, and analytics on Linux-based platforms.
Senior Data Engineer
Senior Data Engineer building international fintech data products — designing integrations with banking systems, building ETL pipelines into Data Lake/DWH, and developing BI data marts in Superset and PowerBI using PostgreSQL, ClickHouse, Python and Airflow.
Data Governance Data Business Analyst
This hybrid Data Governance Data Business Analyst improves Ford Credit’s governance and metadata capabilities on GCP, using AI, SQL, BigQuery, Dataplex, Power BI, and Excel to support discovery, privacy classifications, access controls, compliance, and audits.
Инженер данных/Data Engineer
Designs end-to-end analytical solutions (ETL/ELT, custom BI visualizations, ML models, PWA) for a federal Russian real estate developer, working with 1C, APIs, PostgreSQL, ClickHouse, Python, Apache Airflow, dbt, JavaScript/D3.js, Visiology, and Apache Superset.
Data Engineer
Data Engineer at Numentica working remotely from Saidapet (Chennai, India) to automate data engineering workflows, build data infrastructure, design ETL pipelines, implement data governance and testing, and deploy cloud data solutions.
Data Engineer/ MLOpsE
This role develops, maintains, and optimizes ETL processes on banking platforms, deploys data-science models into production, and supports their operation. It uses Python, Hadoop, Spark, Airflow, data warehouses/Greenplum, Jenkins/Bitbucket/Git CI/CD, and container orchestration.