Engineer - Data Engineering & Analytics

Job Description Implement real-time ETL/ELT pipelines on enterprise data platforms, including Databricks, Snowflake, Microsoft Fabric, Cloudera, Informatica IDMC, or Oracle Implement data workflows using technologies such as Databricks Lakeflow, Fabric Data Factory, Azure Data Factory, Informatica Cloud Data Integration, Snowflake Streams & Tasks, and Apache Airflow Implement Change Data Capture (CDC) and streaming ingestion using one or more technologies, including Oracle GoldenGate, Apache Kafka, and Spark Structured Streaming Apply dimensional data modelling, including Kimball star schemas, to deliver analytics-ready data marts Implement data governance, security, data quality, and lineage using Databricks Unity Catalog, Microsoft Purview, Cloudera SDX, and Informatica Data Quality Apply DataOps practices, including Git-based version control, CI/CD for data pipelines, automated testing, and Infrastructure as Code Monitor, troubleshoot, and optimise production pipelines for performance and cloud cost efficiency, supporting the practice's 99.90% uptime SLA commitment Work directly with client stakeholders throughout the delivery lifecycle, including requirements gathering, data model validation, User Acceptance Testing (UAT), Go-Live, and post-Go-Live SLA support Person Specification Possess a Bachelor's Degree in Data Science or a higher qualification, such as an MSc in Data Science, Data Engineering, or Artificial Intelligence, from a recognised university Have 2–3 years of professional experience in building and operating enterprise data pipelines, data warehouses,

Source: Himalayas