{"id":2130473,"url":"https://alion.io/job/ibm-data-engineer-data-platforms-google-4","title":"Data Engineer-Data Platforms-Google","company":{"id":86,"name":"IBM","domain":"ibm.com","url":"https://alion.io/company/ibm","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"IBM Careers","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"BigQuery","optional":false},{"name":"dbt","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google Bigtable","optional":false},{"name":"Google Cloud Spanner","optional":false},{"name":"Hadoop","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false}],"status":"live","first_seen_at":"2026-09-29T00:00:00Z","employer_posted_date":"2026-10-13","last_verified_at":"2026-10-13T14:53:17Z","board_verified":true,"closed_at":null,"days_open":14,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":14},"description":"A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. As a Data Engineer specializing in Google's data platforms, you will design, build, and maintain data engineering solutions on Google's Cloud ecosystem. This role requires expertise in utilizing various Google services for batch and real-time data pipelines, data migration, and data layer design. Your primary responsibilities will include:\nDesign Data Pipelines: Design and develop batch and real-time data pipelines for Data Warehouse and Datalake using Google services such as DataProc, DataFlow, PubSub, BigQuery, and Big Table.\nDevelop Data Engineering Solutions: Utilize Google Cloud Storage, BigTable, BigQuery DataProc with Spark and Hadoop, and Google DataFlow with Apache Beam or Python to build and maintain data engineering solutions.\nManage Data Platforms: Schedule and manage the data platform using Google Cloud Scheduler and Cloud Composer (Airflow), ensuring efficient data pipeline operations.\nImplement Data Migration: Develop and implement data migration solutions using Google services, ensuring seamless data transfer between systems.\nOptimize Data Layer: Design and optimize the data layer using Google services such as BigQuery, Big Table, and Cloud Spanner, ensuring efficient data storage and retrieval.\nGoogle Cloud Ecosystem Expertise: Exposure to designing, building, and maintaining data engineering solutions on Google's Cloud ecosystem, including services such as Google DataProc, DataFlow, PubSub, BigQuery, Big Table, Cloud Spanner, CloudSQL, and AlloyDB.\nData Pipeline Development Experience: Exposure to developing and managing batch and real-time data pipelines for Data Warehouse and Datalake using Google services and open-source technologies like Apache Airflow, dbt, Spark/Python, or Spark/Scala.\nGoogle Cloud Services Proficiency: Experience working with Google Cloud Storage, BigTable, BigQuery DataProc with Spark and Hadoop, and Google DataFlow with Apache Beam or Python to build and maintain data engineering solutions.\nData Platform Management Knowledge: Exposure to scheduling and managing the data platform using Google Cloud Scheduler and Cloud Composer (Airflow) for efficient data pipeline operations.\nData Layer Design Understanding: Experience working with data layer design using Google services such as BigQuery, Big Table, and Cloud Spanner for efficient data storage and retrieval.\nOpen Source Technologies: Exposure to utilizing open-source technologies like Apache Airflow, dbt, Spark/Python, or Spark/Scala for developing and managing batch and real-time data pipelines.\nData Migration Solutions: Experience working with Google services to develop and implement data migration solutions, ensuring seamless data transfer between systems.\nCloud Composer Expertise: Exposure to using Cloud Composer (Airflow) for scheduling and managing the data platform, ensuring efficient data pipeline operations. 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