Databricks Data Engineer

Total Experience: 6+yrs (min 3+yrs in Databricks)

Notice: Immediate only

Location: Bangalore (Hybrid)/Rest of India- Remote)

If interested, pls share your resume at hiring@growtharc.com

ABOUT THE ROLE

We are looking for experienced Data Engineers to join a high-impact engagement building an AI-driven data platform from scratch. You will design accelerators, define self-service frameworks for a growing user base, and own end-to-end pipeline delivery from enterprise source systems. Requirements will evolve you are expected to drive clarity, not wait for it.

WHAT YOU WILL DO

• Design and build reusable data engineering accelerators and self-service frameworks on Databricks
• Build end-to-end pipelines ingesting from enterprise systems including Bullhorn, Beeline, and SAP Fieldglass
• Lead Unity Catalog adoption data discovery, lineage, access control, and sharing standards
• Build API/MCP integrations enabling programmatic access to the data platform
• Develop dbt models and semantic layer components for commercial and operational reporting
• Embed AI tooling into development workflows and data pipeline design

TECHNICAL REQUIREMENTS

Databricks — Non-Negotiable

• Production experience with Spark, Delta Lake, Workflows, DLT, and Repos
• Unity Catalog implementation and governance
• Performance tuning: partitioning, Z-ordering, caching, cluster configuration, AQE

Python & SQL — Mandatory

• Strong Python: OOP, testing (pytest), modular design, packaging
• Advanced SQL: window functions, CTEs, query optimisation at scale
• PySpark: DataFrame API, UDFs, Structured Streaming

Data Modelling & dbt

• dbt Core or Cloud: models, macros, testing, documentation, semantic layer
• Medallion architecture (bronze/silver/gold) and lake house design principles

Cloud & Infrastructure

• Hands-on with AWS, Azure, or GCP — IAM, storage, secrets management, networking
• CI/CD pipelines with Git-based workflows (GitHub Actions, Azure DevOps, or equivalent)

Data Security

• Row/column-level security, dynamic data masking, audit logging
• Secrets and credential management in cloud-native environments

AI & Emerging Tooling

• Practical experience with LLM APIs, prompt engineering, or AI-assisted development

SOURCE SYSTEM EXPERIENCE (ADVANTAGE)

• Bullhorn (ATS/CRM) — API-based extraction and data model familiarity
• Beeline — VMS platform, reporting exports, integration patterns
• SAP Fieldglass — contingent workforce data, API or file-based ingestion

WHO YOU ARE

• Independent — you deliver with incomplete requirements and drive clarity yourself
• Proactive — you identify gaps, raise concerns early, and propose solutions without being asked
• Fast finisher — you ship working solutions and iterate; you don't over-engineer
• Communicator — clear with technical and non-technical stakeholders alike
• Integrity & work ethic — non-negotiable, no exceptions
• Curious learner — you follow the field and adapt quickly as AI tooling evolves

NICE TO HAVE

• Kafka or event-driven architecture experience
• Terraform or Pulumi for infrastructure management
• Prior consulting or client-facing delivery experience
• Staffing, HR tech, or workforce management industry background

Great attitude is a must. Integrity and work ethic are non-negotiable.