Description

Lead complex data engagements on cloud platforms, focusing on data lakes, engineering, migration, and business intelligence.

This role is hybrid.

Responsibilities

• Design and develop distributed, high-volume batch, real-time, and event-processing systems.
• Translate business requirements into functional specifications, ensuring availability, scalability, security, and resilience.
• Own end-to-end project delivery, maintaining schedule, quality, and customer satisfaction standards.
• Implement data validation and monitoring processes to ensure production data accuracy and availability.
• Mentor junior talent and serve as a technical advisor for complex cloud and data challenges.

Required Skills

• 15+ years in technical, solutioning, and analytical roles.
• 5+ years building and managing Data Lakes, Data Warehouses, and Data Integration on GCP, AWS, or Azure.
• Architecting end-to-end data pipelines for structured and unstructured data.
• Proficiency with ETL and data integration tools: Spark, PySpark, Scala, Dataflow, Dataproc, EMR.
• Experience with traditional ETL tools such as Informatica, DataStage, OWB, or Talend.
• Hands-on experience with cloud and on-premise databases (e.g., Cloud SQL, Spanner, RDS, Aurora, Oracle, Teradata, MySQL).
• Knowledge of NoSQL databases like MongoDB, Cassandra, or Graph DB.
• Practical knowledge of storage and pipeline tools: S3, Cloud Storage, Athena, Glue, Sqoop, Flume, Hive, Kafka, Pub-Sub, Kinesis, Airflow.
• Strong understanding of IaaS, PaaS, SaaS, containers, and microservices architecture.

Preferred Skills

• Experience with Machine Learning frameworks such as TensorFlow or PyTorch.
• Familiarity with BI reporting tools like Looker, Tableau, Power BI, or Superset.

Key Skills

Education

Any Graduate