The Data Engineer will work in a fast-paced, collaborative environment to design, implement, and maintain robust data pipelines and architectures that support data ingestion, processing, and analysis. The ideal candidate will be a skilled problem-solver with experience in developing scalable, high-performance data infrastructure that aligns with business objectives.

Preferred Location - Mohali/Noida/Bengaluru

Key Responsibilities:

• Data Pipeline Design & Development: Architect, design, and implement efficient and scalable data pipelines to process, integrate, and transform diverse data sets from various sources.
• Data Storage & Management: Build and maintain data lakes, warehouses, and other data storage solutions, ensuring they are optimized for both performance and cost efficiency. Manage the CDC and ETL lifecycle, from extraction to transformation to loading.
• Collaborative Problem Solving: Partner with data architects, analysts, and business stakeholders to identify data needs and provide data solutions that empower teams with actionable insights.
• Data Quality & Integrity: Ensure data quality, integrity, and security by establishing robust monitoring systems and applying best practices in data governance.
• Process Optimization & Automation: Streamline data workflows, automate repetitive tasks, and continuously improve system performance to meet evolving business requirements.
• Continuous Improvement: Stay abreast of the latest trends and technologies in data engineering, and incorporate best practices to optimize the overall data ecosystem.
• Troubleshooting & Support: Actively monitor data pipelines and systems, troubleshoot issues, and provide solutions to maintain uninterrupted and efficient data flow.

Required Skills & Qualifications:

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related discipline. Equivalent professional experience is also acceptable.
• Proven experience (5+ years) as a Data Engineer or in a similar role, with a focus on data pipeline construction, integration, and optimization.
• Proficiency in SQL and extensive experience with relational databases such as PostgreSQL, MySQL, MariaDB and cloud-based databases like Amazon Redshift, AWS Aurora and RDS
• Hands-on experience with data engineering tools and frameworks such as Apache Spark, Apache Kafka, Apache NiFi, Debezium,AWS Glue, AWS DMS, AWS Kinesis and the like wise.
• Strong programming skills in Python, or Java with experience in building and deploying production-grade data pipelines.
• Solid understanding of cloud platforms such as AWS, Azure, or Google Cloud, and experience using cloud-native data tools.
• Familiarity with data modeling principles and building efficient, scalable data architectures.

Preferred Qualifications:

• Experience with containerization technologies (e.g., Docker, Kubernetes) for data pipeline deployment and orchestration.
• Knowledge of CI/CD practices and automation tools to enhance the development and deployment of data workflows.
• Familiarity with data visualization tools (e.g., Tableau, Power BI, Apache Superset) to support analytical decision-making.
• Understanding of machine learning workflows and how to optimize data pipelines to support AI/ML initiatives.
• Ability to work in an Agile environment and prioritize tasks based on business needs.