Senior Consultant (Databricks)
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 18h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 64d ago
The date the source published, not the day we noticed it (2026-07-13). Last seen at its source 1h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
India
The description states no restriction of its own. This is the source's own tag.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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workable employer's own board first seen 6d ago · last seen 1h ago
The listing
Job Summary
We are seeking an experienced Senior Consultant – Databricks to design, develop, and optimize modern data platforms on Databricks. The ideal candidate will have strong expertise in data engineering, cloud technologies, ETL development, and big data processing. You will collaborate with cross-functional teams to build scalable, secure, and high-performance data solutions that support analytics, AI, and business intelligence initiatives.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Databricks.
- Build and optimize ETL/ELT workflows using PySpark and Spark SQL.
- Develop and manage Delta Lake architecture for reliable and efficient data processing.
- Integrate data from multiple sources including databases, APIs, streaming platforms, and cloud storage.
- Collaborate with business stakeholders, data analysts, and data scientists to understand business requirements.
- Optimize Spark jobs for performance, scalability, and cost efficiency.
- Implement data quality, governance, and security best practices.
- Monitor production workloads and troubleshoot performance issues.
- Automate deployment processes using CI/CD pipelines.
- Mentor junior team members and provide technical guidance during project delivery.
Required Skills
- Strong experience with Databricks Platform.
- Hands-on expertise in Apache Spark, PySpark, and Spark SQL.
- Experience with Delta Lake, Unity Catalog, and Databricks Workflows.
- Strong SQL programming and data modeling skills.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
- Experience working with data lakes, data warehouses, and modern data architectures.
- Knowledge of orchestration tools such as Azure Data Factory (ADF), Apache Airflow, or similar.
- Experience with version control tools such as Git.
- Understanding of CI/CD practices and DevOps concepts.
- Excellent analytical, troubleshooting, and problem-solving skills.