Assistant Manager - Data Engineer

Assistant Manager

• Data Engineer

We are looking for an experienced

• Data Engineer to design, build, and maintain scalable data pipelines and
• infrastructure that power analytics, reporting, and machine learning
• initiatives across the organization. The ideal candidate has a strong foundation
• in data modeling, distributed systems, and cloud-based data platforms, with a
• track record of delivering reliable, high-performance data solutions.

Key Responsibilities

• ●Design, build, and optimize scalable
• ETL/ELT pipelines to ingest, transform, and load data from diverse sources
• (databases, APIs, streaming platforms, third-party systems)
• ●Develop and maintain data
• warehouse/data lake architectures, ensuring data quality, consistency, and
• reliability
• ●Collaborate with data scientists,
• analysts, and product teams to understand data requirements and deliver
• well-structured, accessible datasets
• ●Build and maintain batch and
• real-time streaming data pipelines using tools like Apache Spark, Kafka, or

Airflow

• ●Implement data quality checks,
• monitoring, and alerting to ensure pipeline reliability and data integrity
• ●Optimize database and query
• performance for large-scale datasets
• ●Design and maintain data models
• (conceptual, logical, physical) and schemas that support analytics and
• application needs
• ●Work with cloud platforms
• (AWS/Azure/GCP) to manage data infrastructure, storage, and compute resources
• ●Implement and enforce data
• governance, security, and compliance best practices
• ●Participate in code reviews, CI/CD
• pipeline development, and infrastructure-as-code practices
• ●Document data pipelines,
• architecture, and processes for team knowledge sharing
• ●Troubleshoot and resolve production
• data pipeline issues in a timely manner

Required Skills &

• ●Bachelor's degree in Computer
• Science, Engineering, or a related field
• ●4–6 years of hands-on experience as a
• Data Engineer or in a similar role
• ●Strong programming skills in Python
• and/or Scala; solid SQL expertise
• ●Experience with ETL/ELT tools and
• orchestration frameworks (Apache Airflow, dbt, Luigi, or similar)
• ●Hands-on experience with big data
• technologies (Apache Spark, Hadoop, Kafka)
• ●Proficiency with relational databases
• (PostgreSQL, MySQL, SQL Server) and NoSQL databases (MongoDB, Cassandra,

DynamoDB)

• ●Experience working with cloud data
• platforms and services (AWS Redshift/Glue/S3, Azure Data Factory/Synapse, GCP BigQuery/Dataflow)
• ●Solid understanding of data modeling
• concepts — entity relationships, cardinality, normalization, and dimensional
• modeling (star/snowflake schemas)
• ●Experience with data warehousing
• solutions (Snowflake, Redshift, BigQuery, Databricks)
• ●Familiarity with version control
• (Git) and CI/CD practices
• ●Understanding of data governance,
• security, and privacy best practices (GDPR, data masking, access controls)
• ●Strong problem-solving skills and
• ability to work with large, complex datasets
• ●