About the Role

We're hiring an experienced Data Engineer with expertise in Data Engineering, ETL/ELT Development, Data Pipelines, Cloud Data Platforms, Data Warehousing, Big Data, and Data Integration. This role is ideal for professionals experienced in designing, building, and optimizing scalable data pipelines for structured and unstructured data across cloud environments such as AWS, Azure, or GCP.

If you have hands-on experience with Python, SQL, Apache Spark, Databricks, Snowflake, Redshift, Data Lakes, APIs, JSON, XML, and cloud-native data engineering, this is an excellent opportunity to work on enterprise-scale data integration and analytics projects.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines for structured and unstructured data.

• Build cloud-based data integration solutions using AWS, Azure, or Google Cloud Platform (GCP).

• Develop reusable data pipelines for heterogeneous data ingestion across multiple enterprise data sources.

• Design and maintain Data Warehouses and Data Lakes using platforms such as Snowflake, Amazon Redshift, and Databricks.

• Build high-performance data processing solutions using Apache Spark and cloud technologies.

• Perform data extraction, transformation, validation, and loading while ensuring data quality and integrity.

• Develop APIs and integrate multiple enterprise systems using JSON, XML, and REST APIs.

• Collaborate with cross-functional stakeholders to gather business requirements and deliver scalable data solutions.

• Create dashboards, reports, KPIs, and data visualizations to support business decision-making.

• Maintain version control using GitHub/GitLab and support CI/CD deployment using Jenkins.

• Troubleshoot, optimize, and enhance data engineering processes while driving continuous improvement initiatives.

Qualifications

• Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Life Sciences, or a related discipline.

• Minimum 8+ years of overall experience, including 5+ years in Data Engineering.

• Strong experience building enterprise Data Pipelines, ETL/ELT workflows, and Data Integration solutions.

• Hands-on expertise in Python and/or R, SQL, and NoSQL databases.

• Experience with cloud platforms such as AWS, Azure, or GCP.

• Experience with Apache Spark (Databricks), Snowflake, Amazon Redshift, or similar data platforms.

• Strong knowledge of Data Warehousing, Data Lakes, Data Modeling, Data Quality, and Data Governance.

• Experience with GitHub/GitLab, Jenkins, APIs, XML, and JSON.

• Strong analytical, problem-solving, stakeholder management, and project management skills.

Benefits

• Opportunity to work on enterprise-scale cloud data engineering and analytics projects.

• Exposure to modern cloud technologies, big data platforms, and enterprise data architecture.

• Career growth with one of India's leading technology and business services organizations.

• Competitive salary package up to ₹16–17 LPA.

Eligibility (Non-Negotiable)

• Minimum 8+ years of overall experience with at least 5+ years in Data Engineering is mandatory.

• Hands-on experience with Python/R, SQL, NoSQL, ETL/ELT, Data Pipelines, and Cloud Platforms (AWS, Azure, or GCP) is mandatory.

• Experience with Data Warehouses, Data Lakes, Apache Spark (Databricks), Snowflake, or Amazon Redshift is highly preferred.

• Graduation is mandatory.

• PAN and Date of Birth (DOB) are mandatory for profile creation.

• Your CV should clearly reflect all the mandatory technical skills and relevant project experience. Profiles that do not demonstrate the required experience may not be considered for review.

Apply now by sharing your updated CV along with your PAN, Date of Birth, Current CTC, Expected CTC, Notice Period.