Big Data Engineer

Required Qualifications :

Familiarity with the Technology stack available in the industry for data management, data ingestion, capture, processing and curation ETL development experience with strong SQL background, analyze huge data sets, trends and issues, and create structured outputs.

Experience in building high-performing data processing frameworks leveraging Google Cloud Platform.

Experience in building data pipelines supporting both batch and real-time streams to enable data collection, storage, processing, transformation and aggregation.

Experience in utilizing Google Cloud Platform Services like Big Query, Composer, Dataflow, Pub-Sub, Cloud Monitoring.

Experience in performing ETL and data engineering work by leveraging multiple google cloud components using Dataflow, Data Proc, BigQuery.

Experience in scheduling like Airflow, Cloud Composer etc.

Experience in Hadoop Big data ecosystem Spark - Batch & Streaming (Python, Scala ) Apache Kafka hands on experience.

Experience in developing both batch and real-time streaming data pipelines Python / Shell scripting.

Nice to have Qualifications :

Strong understanding towards Kubernetes, Docker containers and to deploy Google Cloud Platform services is a plus.

Knowledge of Scrum / Agile development methodologies is a plus.

Any experience with Spark, PySpark, or Kafka is a plus.

Data analysis / Data mapping skills is a plus.

Knowledge in data manipulation JSON and XML.

Technical Skills :

Google Cloud Platform Services : DataFlow, BigQuery, Cloud Storage, DataProc, Airflow, Composer, Pub / Sub and Memorystore / Redis.

Programming languages : Java, Python.

Database : Teradata, BigQuery / BigTable.