Roles & responsibilities
Developing Contemporary Data Warehouse solutions using Databricks and AWS/ Azure Stack
Ability to provide solutions that are forward-thinking in data engineering and analytics space
Collaborating with DW/BI leads to understanding new ETL pipeline development requirements.
Triage issues to find gaps in existing pipelines and fix the issues
Work with businesses to understand the need in the reporting layer and develop a data model to fulfill
reporting needs
Help joiner team members to resolve issues and technical challenges.
Drive technical discussion with client architects and team members
Orchestrate the data pipelines in the scheduler via Airflow
Qualification & experience
Bachelor's and/or master's degree in computer science or equivalent experience.
Must have a total of 6+ yrs. of IT experience and 3+ years' experience in Data warehouse/ETL projects.
Deep understanding of Star and Snowflake dimensional modeling.
Strong knowledge of Data Management principles
Positive understanding of Databricks Data & AI platform and Databricks Delta Lake Architecture
Should have hands-on experience in SQL, Python, and Spark (PySpark)
Candidate must have experience in AWS/ Azure stack
Desirable to have ETL with batch and streaming (Kinesis).
Experience in building ETL / data warehouse transformation processes
Experience with Apache Kafka for use with streaming data / event-based data
Experience with other Open-Source big data products Hadoop (incl. Hive, Pig, Impala)
Experience with Open Source non-relational / NoSQL data repositories (incl. MongoDB,
Cassandra, Neo4J)
Experience working with structured and unstructured data including imaging & geospatial data.
Experience working in a Dev/Ops environment with tools such as Terraform, CircleCI, and GIT.
Proficiency in RDBMS, complex SQL, PL/SQL, Unix Shell Scripting, performance tuning, an troubleshooting.
Databricks Certified Data Engineer Associate/Qualified