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Salary
≈ $21k – $42k per year (Estimated)
Location
In office (Pune)
Seniority
Senior · 6+ years exp

First seen by Alion on Sep 2, 2026.

Overview
Company
Impact
Profile match
SP Staffing services is one of the leading recruitment companies in Chennai, India offering hiring solutions for all industry verticals. Call us.

Key Responsibilities :

- Design, build, and optimize scalable, reliable, and efficient ETL/ELT pipelines for processing large datasets.

- Automate data workflows to ensure real-time and batch data availability.

- Develop and manage data solutions using Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure SQL.

- Work with AWS services such as AWS Glue, Amazon Redshift, Amazon S3, AWS Lambda, and Amazon Athena to build robust data solutions.

- Integrate structured, semi-structured, and unstructured data from multiple sources.

- Create and maintain data models to support analytics and reporting requirements.

- Work closely with Data Scientists, Data Analysts, Software Engineers, and other cross-functional teams.

- Translate business requirements into technical specifications and scalable data solutions.

- Manage IAM roles, policies, and encryption for data at rest and in transit.

- Mentor and guide junior data engineers within the team.

- Apply AI/ML and Generative AI capabilities to data engineering use cases where applicable.

- Monitor and optimize the performance of cloud data pipelines and infrastructure.

- Debug and resolve data-related issues in a timely manner.

Required Qualifications :

- Bachelor's degree in Computer Science, Engineering, or a related field.

- 6 - 11 years of hands-on experience in cloud data engineering, with strong exposure to Azure and AWS.

- Strong experience with Azure Databricks and AI/ML workloads.

- Proficiency in Python, SQL, and scripting languages for data manipulation and automation.

- Experience with data orchestration tools such as Apache Airflow and relevant cloud services.

- Strong understanding of distributed computing and big data frameworks, including Apache Spark and Hadoop.

- Knowledge of cloud data warehouses such as Azure Synapse Analytics and Snowflake.

- Experience with CI/CD pipelines for data workflows using Jenkins, GitHub Actions, or Azure DevOps.

- Relevant Azure, AWS, and/or Databricks certifications are preferred.

- Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.

- Strong problem-solving skills with the ability to work independently and collaboratively.

Preferred Candidate Profile :

- Strong hands-on experience delivering enterprise-scale cloud data engineering solutions.

- Experience working across both Azure and AWS cloud environments.

- Good understanding of modern data architecture, data governance, security, and cloud best practices.

- Exposure to AI/ML and Generative AI applications within data engineering.

- Strong communication, mentoring, and stakeholder-management skills.

Skills

Azure, Data Engineering, ETL, Azure Data Factory, Synapse Analytics, Azure Databricks, Azure SQL, Python, SQL

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