Overview

Responsibilities:
  • Data Warehouse & Platform Development – Develop and optimize data objects and components across enterprise data platforms, ensuring high performance and scalability
  • Data Modeling – Design and implement logical and physical data models aligned with architectural, technical, and business requirements
  • Data Pipelines – Develop and maintain ETL/ELT processes and integrations for structured and semi-structured data from multiple sources
  • Real-Time Processing – Implement and maintain real-time/streaming ingestion and solutions for business use cases
  • Report Development – develop reports when needed
  • Analytics Enablement – Deliver clean, optimized datasets for analytics and reporting
  • Data Quality – Implement validation, cleansing, and monitoring practices to ensure accuracy, consistency, and reliability of data across its lifecycle
  • Continuous Improvement – Contribute to evaluating and adopting modern tools, methods, and technologies that improve performance, scalability, and reliability
Required Qualifications:
  • BS degree (preferably Computer Science or equivalent)
  • 3–5 years of experience in data engineering, integration, or database development
  • Strong SQL development skills and experience with relational databases (MS SQL Server, PostgreSQL, or Oracle)
  • Familiarity with ETL/ELT processes and data pipeline tools (e.g., SSIS, Airflow, Spark etc.)
  • Knowledge of data warehousing concepts (star/snowflake schemas, normalization, indexing)
  • Experience with scripting (Python or similar)
  • Understanding of data quality, metadata, and security concepts
  • Familiarity with version control (Git) and CI/CD
Nice To Have:
  • Experience with Power BI or similar tools
  • Exposure to cloud or modern data platforms (e.g. Data Lakehouse, Data Lake, Kafka)
Technologies:
  • MS SQL Server
  • PostgreSQL
  • Oracle
  • SSIS
  • Airflow
  • Spark
  • Power BI
  • Python
  • Git
  • Data Lakehouse
  • Data Lake
  • Kafka
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