Hire Top Data Pipeline Engineers in India!
Years of experience
Customer satisfaction
What Makes Benchkart a Great Partner for Hiring Data Pipeline Engineers?
Benchkart blends AI-driven talent intelligence, a deep vendor ecosystem, and Avance Group’s governance to deliver mission-critical pipeline engineering with unmatched reliability and speed.
Security-First Delivery
Enterprise NDAs, governed data flows, encrypted transport, compliance-focused engineering.
Proven Talent Network
Data Pipeline specialists sourced from our bench, passive talent ecosystem, and 2000+ vetted partners.
Growth-Driven Engineering
Engineers focused on scalable ingestion, distributed processing, automation, and long-term maintainability.
Cutting-Edge Tech Stack
Developers bring hands-on expertise in:
Expertise in Kafka
Spark
Airflow
Flink
Beam
Python
SQL
Delta Lake
cloud services (AWS/Azure/GCP)
orchestration
CI/CD, and monitoring
Services We Offer
Batch & Streaming Data Pipeline Development
Data Ingestion & Integration Engineering
Data Lake & Warehouse Pipeline Development
Real-Time Data Streaming & Event Processing
Pipeline Monitoring, Observability & Optimization
Migration & Modernization of Data Workflows
Expertise of Our Data Pipeline Engineers
A capability-first view of what you can expect from Benchkart’s Java engineering talent.
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Apache Spark, PySpark
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Apache Beam, Dataflow
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SQL/NoSQL transformations
Roles & Responsibilities: Data Pipeline Engineers design and optimize distributed workloads, build resilient ETL/ELT pipelines, handle schema evolution, and ensure efficient processing across large datasets.
Apache Kafka
AWS Kinesis, GCP Pub/Sub, Azure Event Hubs
Flink, Spark Streaming, Structured Streaming
Roles & Responsibilities:
They engineer real-time ingestion pipelines, build event-driven systems, tune streaming jobs, manage checkpointing, and ensure exactly-once or at-least-once guarantees.
Apache Airflow, Cloud Composer
Azure Data Factory, AWS Step Functions
CI/CD-driven pipeline promotion
Roles & Responsibilities:
Engineers orchestrate batch and streaming workflows, automate dependencies, implement retries/error handling, and manage workflow observability at scale.
AWS (Glue, EMR, Lambda, S3)
Azure (Databricks, ADF, ADLS)
GCP (BigQuery, Dataflow, GCS)
Roles & Responsibilities:
They design pipelines tailored to cloud-native architectures, integrate platform-specific services, optimize cost/performance, and maintain secure, modular workloads.
Data lakes, lakehouse architectures
Parquet, Delta Lake, ORC formats
Partitioning, clustering, indexing
Roles & Responsibilities:
Pipeline engineers structure data for analytics readiness, optimize file formats, organize medallion layers, and ensure high-quality data delivery to warehouses and BI tools.
Unit/integration tests for pipelines
Observability (Prometheus, Grafana, CloudWatch)
Data quality checks, lineage, DQ frameworks
Roles & Responsibilities:
They enforce validation rules, ensure pipeline reliability, implement dashboards and alerts, maintain SLA compliance, and proactively resolve performance bottlenecks.
How We Hire Developers
With a structured multi-stage hiring process, we onboard only high-calibre Data Pipeline Engineers.
Skill Benchmarking
Thorough CV & background evaluation
Human Vetting
Interview with HR specialist
Experience Validation
Communication & soft-skills assessment
Cultural Fit
Technical interview with senior data architect
Hire Developers from Benchkart
STEP 1 Inquiry
We understand your ingestion volumes, latency requirements, integrations, cloud environment, and analytics goals.
STEP 2 Developer Selection
AI-matched profiles curated from our bench, partner network, and passive pipeline-engineering talent.
STEP 3 Integration
Engineers join your cloud environment, repos, workflow orchestrators, and sprint cycles seamlessly.
STEP 4 Scaling
Scale pipeline engineering capacity with governed delivery, continuity frameworks, and account oversight.
Choose the Right Development Model for Your Business
Flexible engagement models tailored to large-scale pipeline development and modernization.
Data Pipeline Engineering Team Augmentation
Boost engineering velocity instantly with skilled pipeline developers.
Dedicated Data Pipeline Engineering Squad
A full-time team aligned exclusively to your ingestion and analytics roadmap.
Full Pipeline Development Outsourcing
We own architecture → development → orchestration → DevOps → monitoring.
Top Reasons to Choose Benchkart for Data Pipeline Engineer Hiring
Quality + speed + governance built for enterprise delivery.
Top Reasons to Choose Benchkart for ETL Developer Hiring
AI-powered talent matching backed by enterprise governance and delivery rigor.
Unmatched Speed 48-Hour Shortlists
Receive curated Data Pipeline Engineer profiles within 48–72 hours.
Massive Vendor Ecosystem 2000+ Strong
Tap into India’s strongest governed network for data engineering and cloud modernization talent.
Wisestep ATS + CRM Skill-First Precision
AI ranks candidates based on pipeline architecture depth, streaming skills, cloud readiness, and performance optimization.
Bench-Ready Pipeline Engineers
Skilled across Spark, Kafka, Beam, Airflow, cloud services, workflow automation, and Lakehouse patterns.
Governed Delivery with Enterprise SLAs
Quality gates, lineage documentation, cost governance, and production-hardening frameworks.
Backed by Avance Group Global Trust
Operating across 13+ countries with long-standing enterprise delivery success.
Need a Dedicated Data Pipeline Engineering Team?
Hire pre-vetted engineers who build reliable, scalable, and production-grade data pipelines from day one.
Shortlist in 48 hours. Onboarding in 5–10 days.
Operates across
Industries We Support for Data Pipeline Engineer Hiring
Benchkart enables large-scale data ingestion and analytics across industries.
BFSI & FinTech
Healthcare
E-commerce
Manufacturing
SaaS
Logistics
Telecom
Hospitality
FAQs
1. What does a Data Pipeline Engineer do?
They build robust data ingestion systems, streaming/batch pipelines, and integration workflows that move, validate, and prepare data for analysis.
2. What skills should a Data Pipeline Engineer have?
Spark, Kafka, Python, SQL, Airflow, Beam, cloud services, orchestration, data modeling, and performance tuning.
3. Are Pipeline Engineers different from ETL Developers?
Yes, Pipeline Engineers focus on distributed, cloud-native, streaming/batch systems; ETL Developers focus on structured, tool-based ETL workflows.
4. How much does it cost to hire a Data Pipeline Engineer in India?
Typically $25–$60 per hour, depending on cloud platform experience and pipeline complexity.
5. Can Benchkart deliver candidates in 48 hours?
Yes, most shortlist deliveries occur within 48–72 hours.
6. Can I hire a full Data Pipeline Engineering team?
Yes, including pipeline engineers, data engineers, architects, DevOps, and QA.
7. Will engineers work in my time zone?
Yes, overlapping hours with US, UK, EU, and ME clients can be arranged.
8. Do you support pipeline modernization and cloud migration?
Yes, including Spark modernization, Kafka adoption, and cloud-native pipeline redesign.
9. How do you ensure pipeline reliability?
Through retry logic, error handling, lineage, DQ frameworks, CI/CD, and governed monitoring.
10. Why hire Data Pipeline Engineers from Benchkart?
You gain access to top-tier talent enhanced by AI vetting, governed delivery, and SLA-backed execution.
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