Data /Engineer /Lead /Project Manager /Architect

We are Hiring: Data Engineers Enterprise Data Platforms & Analytics

(50+ Openings | Yrs Exp | Multiple Levels)

Location: Mumbai / Pune / Chandigarh / Bengaluru / Gurugram / Noida / New Delhi / Kolkata / Hyderabad . Chennai ( Remote and Hybrid options are available for some roles)

Industry: Fortune 500 Client Projects (Staffing via Hatchtra Innotech Pvt. Ltd.)

Employment Type: Full-Time / Contract (C2H)

About us:

Hatchtra is a leading staffing and workforce solutions company, trusted by Fortune 500 organizations and global enterprises to build their technology teams.

When you join us, you'll work directly with our Fortune 500 client teams that power mission-critical systems worldwide.

About the Role

We are looking for Data Engineers (3-20 years) to design, build, and maintain scalable data pipelines and enterprise data platforms. This role is ideal for engineers passionate about big data, cloud data platforms, ETL/ELT processes, and analytics engineering to support global enterprises in their digital transformation journey.

From data ingestion to advanced analytics enablement, you will play a critical role in turning raw data into actionable insights.

Open Positions & Designations

• Associate Data Engineer (3-5 Yrs)
• Data Engineer / Senior Data Engineer (5-10 Yrs)
• Lead Data Engineer / Analytics Engineer (812 Yrs)
• Data Engineering Manager / Solutions Architect (1015 Yrs)
• Director – Data Platforms & Engineering (15–20 Yrs)

Key Responsibilities

Scale with Level Professional (3–5 Yrs)

• Design and implement ETL/ELT pipelines to integrate data from various sources.
• Build and optimize data warehouses and data lakes on cloud or on-prem platforms.
• Work with SQL, Python, or Scala for data processing and transformation.
• Implement data quality checks and validation frameworks.
• Support analytics teams by making clean, reliable data available.
• Develop basic automation scripts for data ingestion and reporting workflows.

Mid-Level (5–10 Yrs)

• Lead data integration projects across structured, semi-structured, and unstructured data.
• Optimize pipelines for performance, scalability, and cost-effectiveness.
• Implement data modeling best practices for analytics and BI.
• Collaborate with data scientists, analysts, and product teams to enable ML/AI use cases.
• Deploy streaming data pipelines using Kafka, Kinesis, or Azure Event Hub.
• Manage and improve data governance, lineage, and metadata management.

Senior/Leadership (10–20 Yrs)

• Define enterprise data engineering strategy and architecture standards.
• Lead multi-cloud data platform modernization initiatives (AWS, Azure, GCP).
• Build and manage global data engineering teams and delivery models.
• Partner with executives to deliver data-driven transformation programs.
• Oversee compliance, data security, and privacy frameworks (GDPR, HIPAA, SOC2).
• Drive innovation in real-time analytics, serverless data processing, and AI-driven data engineering.

Skills & Tools

• Core Expertise: ETL/ELT Development, Data Modeling, Pipeline Automation, Data Warehousing
• Programming: SQL, Python, Scala, Java
• Data Platforms: Snowflake, BigQuery, Azure Synapse, Amazon Redshift, Databricks
• Orchestration: Apache Airflow, AWS Step Functions, Azure Data Factory, dbt
• Streaming: Kafka, Kinesis, Azure Event Hubs, Spark Streaming
• Big Data Tools: Apache Spark, Hadoop, Hive
• Cloud Expertise: AWS, Azure, GCP (multi-cloud deployments)
• DevOps for Data: Docker, Kubernetes, Terraform, CI/CD for DataOps

• Preferred Certifications:

• Google Professional Data Engineer

• AWS Certified Data Analytics – Specialty
• Microsoft Certified: Azure Data Engineer Associate

Qualifications

• Bachelor's/Master's in Computer Science, Data Engineering, or related field.
• 3+ years of experience in data engineering, ETL/ELT, or data platform development.
• Strong proficiency in SQL, Python/Scala, and cloud-native data services.
• Experience in building scalable, secure, and automated pipelines.
• Proven leadership and strategic architecture experience for senior roles.

Why Join Us?

• Contribute to enterprise-scale data transformation projects.
• Collaborate with Fortune 500 companies and global engineering teams.
• Exposure to cutting-edge cloud data platforms and big data technologies.
• Career growth, certifications, and flexible work options.

How to Apply

For quick consideration, please email your resume and include the desired position and experience level (e.g., "Data Engineer – Mid-Level") in the subject line.