SL Transformation-Senior Data Engineer

• Design, develop, and maintain robust ETL/ELT pipelines for structured and unstructured data.
• Build scalable data ingestion, transformation, and storage solutions using modern data engineering frameworks.
• Develop and optimize data models, data warehouses, and lakehouse architectures.
• Ensure data quality, integrity, security, and governance across data platforms.
• Collaborate with business stakeholders, data analysts, architects, and product teams to understand requirements and deliver solutions.
• Monitor and troubleshoot data pipelines, resolving performance bottlenecks and operational issues.
• Implement CI/CD, automation, and DevOps practices for data engineering workflows.
• Work with cloud-native services and distributed data processing technologies.
• Support data migration and modernization initiatives as part of transformation programs.
• Mentor junior engineers and contribute to technical best practices and standards.

• Strong experience in SQL and data modelling concepts.
• Hands-on experience with ETL/ELT development.
• Proficiency in Python, Scala, or Spark-based data processing.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of Data Warehouse and Data Lake architectures.
• Experience with orchestration tools such as Airflow, ADF, or equivalent.
• Understanding of data governance, data quality, and security practices.
• Familiarity with CI/CD pipelines and version control tools.

Preferred Skills

• Experience with Databricks, Snowflake, Redshift, Synapse, or BigQuery.
• Knowledge of Real Time streaming technologies such as Kafka.
• Exposure to Agile delivery methodologies.
• Experience in large-scale data transformation or modernization programs.
• Expected Competencies
• Strong analytical and problem-solving skills.
• Excellent stakeholder communication and collaboration.
• Technical leadership and mentoring capability.
• Ability to work independently and drive delivery in a fast-paced environment.