Hire Top Databricks Data Engineers in India!
Years of experience
Customer satisfaction
What Makes Benchkart a Great Partner for Hiring Databricks Data Engineers?
Benchkart blends AI-driven talent intelligence, a deep vendor ecosystem, and Avance Group’s governance to deliver enterprise-grade Databricks engineering with unmatched speed and reliability.
Security-First Delivery
Enterprise NDAs, governed cloud access, Unity Catalog compliance, and secure data lifecycle controls.
Proven Talent Network
Databricks-certified engineers sourced from our bench, passive network, and 2000+ vetted partners.
Growth-Driven Engineering
Engineers skilled in large-scale ETL/ELT, streaming pipelines, Delta Lake, optimization, and Lakehouse architecture.
Cutting-Edge Tech Stack
Developers bring hands-on expertise in:
Expertise in Databricks (Azure/AWS/GCP)
PySpark
SQL
Delta Lake
Unity Catalog
MLflow
Airflow
dbt
Kafka
CI/CD
Terraform, and data governance frameworks
Services We Offer
Lakehouse Architecture & Implementation
ETL/ELT Pipeline Development Using Databricks
Performance OptimizData Quality, Observability & Governanceation & Query Tuning
Advanced Analytics & ML-Ready Pipelines
Legacy Data Platform Migration to Databricks
Platform Operations, Optimization & Support
Expertise of Our Databricks Data Engineers
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PySpark, Scala, SQL
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Optimized transformations, wide/deep joins
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Adaptive query execution (AQE)
Roles & Responsibilities: Databricks Data Engineers design and optimize distributed jobs, implement complex transformations, troubleshoot cluster bottlenecks, and deliver high-throughput data pipelines across large datase
ACID transactions
Time Travel & Change Data Feed
Medallion (Bronze/Silver/Gold) architecture
Roles & Responsibilities:
They build robust Lakehouse layers, enforce schema evolution practices, manage transactional reliability, and create scalable, governed data models suited for analytics and ML.
Structured Streaming
Event ingestion via Kafka/Kinesis/Event Hubs
Low-latency pipelines & checkpointing strategies
Roles & Responsibilities:
Engineers build continuous processing systems, manage watermarks/windows, ensure exactly-once semantics, and support business-critical real-time insights.
Databricks Workflows
Airflow, Composer, Azure Data Factory
Job orchestration & dependency management
Roles & Responsibilities:
They automate workflows end-to-end, schedule pipelines, build DAGs, integrate with CI/CD, and ensure resilient and recoverable orchestration for production workloads.
Azure Databricks / AWS Databricks / GCP Databricks
Cloud storage integration (ADLS/S3/GCS)
IAM, networking, and security standards
Roles & Responsibilities:
They integrate Databricks into enterprise cloud environments, manage permissions, optimize cluster configurations, and ensure compliance with cloud security and governance models.
Unity Catalog, Lakehouse governance
Testing frameworks, MLflow, dbt
Cost optimization, cluster right-sizing
Roles & Responsibilities:
Engineers implement data quality pipelines, automate deployments, track lineage, and optimize compute/storage costs while maintaining operational reliability and audit readiness.
How We Hire Developers
With a structured multi-stage hiring process, we onboard only high-calibre Databricks engineers.
Skill Benchmarking
Thorough CV & background evaluation
Human Vetting
Interview with HR specialist
Experience Validation
Communication & soft-skills assessment
Cultural Fit
Technical interview with Databricks Architect
Hire Developers from Benchkart
STEP 1 Inquiry
We assess your data platform goals, ingestion strategy, Lakehouse requirements, and cloud environment.
STEP 2 Developer Selection
AI-matched Databricks profiles sourced from our bench, partners, and passive talent pipelines.
STEP 3 Integration
Engineers join your Databricks workspace, repos, CI/CD pipelines, orchestration tools, and sprint cycles seamlessly.
STEP 4 Scaling
Scale data engineering capacity effortlessly with governed delivery and ongoing account management.
Choose the Right Development Model for Your Business
Flexible engagement models tailored for Lakehouse modernization and enterprise analytics.
Databricks Data Engineering Team Augmentation
Add skilled Databricks engineers instantly to accelerate delivery.
Dedicated Databricks Engineering Squad
A full-time team aligned exclusively to your Lakehouse and analytics roadmap.
Full Databricks Platform Outsourcing
We manage architecture → pipelines → ML integration → DevOps → governance.
Top Reasons to Choose Benchkart for Databricks Data Engineer Hiring
Quality + speed + governance built for enterprise delivery.
Built on Avance Group’s Talent Engine
AI-driven talent mapping supported by enterprise-grade governance.
Unmatched Speed 48-Hour Shortlists
Receive curated Databricks engineer profiles within 48–72 hours.
Massive Vendor Ecosystem 2000+ Strong
India’s strongest governed network for Databricks & cloud data engineering talent.
Wisestep ATS + CRM Skill-First Precision
AI evaluates candidates on PySpark mastery, Lakehouse fluency, cloud expertise, and pipeline architecture.
Bench-Ready Databricks Experts
Proficient in Delta Lake, PySpark, streaming, MLflow, dbt, Airflow, and Databricks Workflows.
Governed Delivery with Enterprise SLAs
Architecture oversight, quality gates, cost optimization guardrails, and continuity frameworks.
Backed by Avance Group Global Trust
Operating across 13+ countries with long-standing delivery success.
Need a Dedicated Databricks Engineering Team?
Hire pre-vetted Databricks data engineers who build scalable, governed, and analytics-ready Lakehouse systems from day one.
Shortlist in 48 hours. Onboarding in 5–10 days.
Operates across
Industries We Support for Databricks Data Engineer Hiring
Benchkart supports modern data platform transformation across key industries.
BFSI & FinTech
Healthcare
E-commerce
Manufacturing
SaaS
Logistics
Telecom
Hospitality
FAQs
1. What does a Databricks Data Engineer do?
They design and operate distributed pipelines, build Lakehouse architectures, optimize Spark workloads, and deliver analytics-ready datasets.
2. Is Databricks good for enterprise-scale data engineering?
Yes, it is one of the leading unified analytics and Lakehouse platforms for large-scale data workloads.
3. What key skills should a Databricks engineer have?
PySpark, Delta Lake, Spark optimization, SQL, streaming, Databricks Workflows, DBFS, cloud integration, and orchestration tools.
4. How much does it cost to hire a Databricks Data Engineer in India?
Typical rates range from $30–$70 per hour, depending on cloud experience and Lakehouse expertise.
5. Can Benchkart provide Databricks engineers within 48 hours?
Yes, curated shortlists usually arrive within 48–72 hours.
6. Can I hire a full Databricks engineering team?
Absolutely, including data engineers, architects, ML engineers, DevOps, and QA.
7. Do Databricks engineers work in international time zones?
Yes, overlapping hours with US, UK, EU, and ME clients are common.
8. Do you support migration to Databricks from Hadoop or legacy pipelines?
Yes, our engineers modernize legacy systems to Spark- and Lakehouse-based architectures.
9. How do you ensure performance and cost optimization?
By tuning jobs, right-sizing clusters, optimizing SQL/Spark, and establishing governance around compute usage.
10. Why hire Databricks engineers from Benchkart?
You get top-tier Lakehouse engineering talent enhanced by AI vetting, governed delivery, and enterprise SLAs.
Get in Touch with Benchkart Reliable Tech Talent Delivery
We’re happy to answer any questions you may have and help you understand how Benchkart can support your technology hiring and delivery needs.
Your benefits:
- Vendor-verified
- Delivery-focused
- AI-driven
- Results-oriented
- Execution-ready
- Transparent
What happens next?
We schedule a quick call at your convenience
We understand your role, timeline, and delivery context
We activate the right talent path