• Build, operationalize, secure, and monitor data processing systems

• Support the development of logical and physical data models in Data warehousing

• Build reliable data pipelines that clean, transform, and aggregate data from multiple systems/ sources

• Understand Architecture and build Streaming ETL and Batch ETL pipelines, following best practices, optimizing queries, pipelines as per the needs

• Work closely with Product Owner and business process owners to translate business requirements into technical solutions

• Build datamarts to cater the needs of Business Intelligence & Reporting and Data Science team.

• Automate manual processes to optimize data delivery

• Use agile software development processes to iteratively make improve deliverables

• Identify internal process improvements and implement them

Ensure accuracy and quality of data movement across ETL pipelines in production environment

Qualifications Hold the control key to add multiple qualifications :

• B.E.

• B.Tech.

• MCA

Certifications :

Google Cloud Platform, Data Engineering

No. of years of experience :

3 to 5 years

Area of professional exposure (functional/technical skills) :

• Bachelor’s degree and/or Master’s degree in Computer Science/Information Technology or related technical field

• 4+ years of industry experience in data ingestion, ETL, data warehousing

• Solid experience on building streaming ETL pipelines (Kafka/Spark)

• 2+ years of experience in GCP environment: Kafka/Spark, GCP pub/sub, Dataflow, BigQuery

• Should have sound experience / knowledge on SQL Query optimization & performance tuning

• Hands on experience in programming languages like Java/Scala/Python, Shell Scripting

• Databases: SQL Server, PostgreSQL, MySQL (one or more required)

• Exposure to Hadoop ecosystem

• Ability to handle semi-structured data (JSON, XML, etc.,)

Functional skills :

Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment