Senior Consultant

Emids Technologies Limited · Remote

Source and collection record

Last observed by our collector: 9 October 2026 at 12:36 am IST. This is not a manual review or a confirmation from the employer.

Employer requisition: RR/967/2026

Job type and experience labels are automated discovery categories. The employer determines eligibility. Original experience wording was not retained separately; check the current employer page.

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Collected role description

We are looking for a Databricks Data Engineer with 6+ years of Data Engineering experience who has strong hands-on experience in Azure Data Services, Databricks, ETL/ELT frameworks, Medallion Architecture, and Data Quality . Must-Have Skills 6+ years of experience in Data Engineering . Strong hands-on experience with Azure Databricks, PySpark, Spark SQL, Python, and SQL . Good understanding and implementation experience of Medallion Architecture – Bronze, Silver, and Gold . Experience with Azure Data Lake Storage (ADLS Gen2), Azure Data Factory (ADF), and Azure SQL/Synapse . Experience developing batch and incremental data pipelines . Understanding of different data ingestion methods , including: File-based Database-based API-based Incremental/CDC Streaming Experience with Delta Lake and performance optimization. Hands-on experience implementing Data Quality checks , including completeness, accuracy, consistency, uniqueness, null checks, duplicates, and source-target reconciliation. Experience with ETL/ELT framework development , error handling, logging, audit, and monitoring. Good understanding of data modeling and data transformation . Experience with Git and CI/CD for data engineering deployments. Good-to-Have Skills Databricks / Azure Data Engineer certification. Experience with Unity Catalog and Databricks governance . Experience with Kafka/Event Hubs and Structured Streaming . Experience with dbt, Fivetran, Informatica, or other ingestion frameworks . Experience with Great Expectations or other Data Quality frameworks . Knowledge of Data Governance, Metadata, Lineage, and Data Catalog concepts. Experience developing metadata-driven/reusable ingestion frameworks .

Collected experience requirement

4-6 years