Design, develop, and operate large scale data pipelines to support internal and external consumers
Improve and automate internal processes
Monitor jobs and pipelines to resolve and/or alert the team
Integrate data sources to meet business requirements
Write robust, maintainable, well documented code

Requirements

2-4 years professional Data Engineering and Data warehousing experience
Extremely strong implementation experience in Python, Parquet, Spark, Azure Databricks, Delta Lake, Databricks Data Warehouse. Databricks workflows, Delta Sharing and Unity Catalog.
Experience managing data ingress (import) and egress (export) processes within Informatica ETL workflows.
SQL development knowledge – Stored procedures, triggers, jobs, indexes, partitioning, pruning etc.
Be able to write/debug complex SQL queries
ETL/ELT and Data-warehousing techniques and best practices
Experience building, maintaining, and scaling ETL/ELT processes and infrastructure
Implementation experience with various data modelling techniques
Implementation experience working with a BI visualization tool (Sisense or Sigma is a plus)
Experience with CI/CD tools (Preferred Gitlab, Jenkins)
Experience with cloud infrastructure (Azure strongly preferred)
Experience working in a fast-paced product environment, with an attitude of getting the job done with the least amount of tech debt
Knowledge of being able to work with a variety of Ingestion patterns such as API/SQL servers etc.
Knowledge of Master Data Management
Prior Financial industry experience a plus
Be able to navigate ambiguity and pivot based on business priorities with ease
Strong communication skills
Be a team player and able to collaborate well

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonParquetSparkAzure DatabricksDelta LakeInformatica ETLSQLETLELTData modeling

Soft Skills

strong communication skillsteam playercollaborationability to navigate ambiguityadaptability