Data /Engineer /Lead /Project Manager /Architect

We are Hiring: Data Engineers Enterprise Data Platforms & Analytics

(50+ Openings | 3 - 20 Yrs Exp | Multiple Levels)

Location:

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

Data Engineers (3-20 years)

data ingestion to advanced analytics enablement

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.