Weekday virtual drive 7 years 21-Aug-26 12-2pm Hyderabad We are pleased to invite you for an interview scheduled on Interview Details:• Date:   21-Aug-2 12-2pm Hyderabd Please share updated resume Name: Contact Number: Email ID: Highest Qualification in: (Eg. B.Tech/B.E./M.Tech/MCA/M.Sc./MS/BCA/B.Sc./Etc.) Current Organization Name: Total IT Experience-7 to 10 yrs LOCATION TCS Hyderabab Current CTC Expected CTC Notice period: Whether worked with TCS - Y/N Please apply only if your skill matches  Digital : Python(MongoDB, Python, Pyspark, Big Query, GCS)  1 Role Mongo db GCP Data Engineer Python Pyspark Developer (BigQuery, Cloud Storage, Dataproc, Airflow) 2 Required Technical Skill Set GCP Data Engineer to design, build, and optimize scalable data pipelines and analytics solutions using BigQuery, Cloud Storage, Dataproc, and Airflow. Desired Experience Range 7 Years Location of Requirement HYDERABAD Immediate Joiners Needed  Desired Competencies (Technical/Behavioral Competency) Must-Have (Ideally should not be more than 3-5) GCP Services: BigQuery, Cloud Storage, Dataproc, Cloud Composer (managed Airflow) or self-managed Airflow. Airflow: Strong experience in DAG creation, operators/hooks, scheduling, backfilling, retry strategies, and CI/CD for DAG deployments. Programming:



Proficiency in Python and Pyspark (PySpark, Airflow DAGs), SQL (advanced BigQuery SQL). Data Modeling: Dimensional modeling (Star/Snowflake), data vault basics, and schema design for analytics. Performance Tuning: BigQuery partitioning/clustering, predicate pushdown, job stats review, Dataproc executor tuning. Version Control & CI/CD: Git, branching strategies, pipelines for deploying Airflow DAGs and config. Operational Excellence: Monitoring with Stackdriver/Cloud Logging, debugging pipeline failures, and root-cause analysis. involves end-to-end ownership of data ingestion, transformation, orchestration, and performance tuning for batch and near real-time workflows. Good-to-Have Streaming: Pub/Sub, Dataflow (Apache Beam) for near real-time pipelines. Orchestration Patterns: Event-driven pipelines, dependency management, and cross-setting promotion. Data Governance: Catalog/lineage tools (e.g., Data Catalog), PII handling, row-level security, column-level encryption. Containers & Infra: Docker, Terraform for IaC on GCP; Kubernetes concepts. BI Integration: Experience integrating with Looker, Tableau, or Power BI. Certifications: Google Professional Data Engineer / Cloud Architect.

📌 Digital : Python(MongoDB, Python, Pyspark, Big Query, GCS) (Telangana)
🏢 Tata Consultancy Services
📍 Telangana