We are seeking a highly skilled and experienced Senior Data Engineer to design, build, and optimize scalable data pipelines and modern data platforms that support analytics, reporting, machine learning, and business intelligence initiatives.

The ideal candidate will have strong expertise in data architecture, ETL/ELT development, cloud data technologies, database systems, and big data processing frameworks.

This role requires close collaboration with Data Scientists, Analysts, Product Teams, and Business Stakeholders to deliver reliable, high-performance, and secure data solutions.

Key Responsibilities :

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

- Build and manage modern data platforms, data lakes, and enterprise data warehouses.

- Develop data ingestion, transformation, integration, and orchestration workflows.

- Optimize database performance, query execution, storage management, and data processing efficiency.

- Implement data quality checks, governance standards, monitoring, and validation frameworks.

- Work with large-scale datasets using distributed processing frameworks and cloud-native technologies.

- Collaborate with Data Scientists and Analytics teams to support machine learning and reporting requirements.

- Design scalable data models, schemas, partitioning strategies, and metadata management solutions.

- Ensure data security, privacy, reliability, and compliance across data systems.

- Support real-time and batch data processing architectures.

- Automate deployment workflows, CI/CD pipelines, and infrastructure provisioning for data platforms.

- Troubleshoot production data issues and implement performance improvements.

- Mentor junior engineers and contribute to engineering best practices and technical strategy.

Required Skills & Qualifications :

- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or related field.

- 5-10 years of experience in Data Engineering or Big Data development.

- Strong programming experience in Python, Scala, Java, or SQL.

- Hands-on experience with ETL/ELT tools and data orchestration frameworks.

- Strong expertise in relational and NoSQL databases such as PostgreSQL, MySQL, MongoDB, Cassandra, or Snowflake.

- Experience with big data technologies such as Apache Spark, Hadoop, Kafka, or Hive.

- Strong knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform.

- Experience with cloud data services such as Redshift, BigQuery, Synapse, Snowflake, or Databricks.

- Familiarity with workflow orchestration tools such as Airflow, Prefect, or Luigi.

- Experience with Docker, Kubernetes, Git, and CI/CD practices.

- Strong understanding of data modeling, warehousing concepts, and distributed systems.

- Excellent analytical, debugging, and problem-solving skills