Data Engineer, Associate/Senior Associate,

Your key responsibilities

• Design, build, and maintain efficient, reusable, and scalable ETL/ELT pipelines for structured and unstructured data.
• Develop and optimize data workflows to support advanced analytics, machine learning models, and reporting tools.
• Collaborate with data scientists, analysts, and business stakeholders to gather requirements and ensure data quality and availability
• Work with cloud and on-prem data platforms (e.g., AWS, Azure, GCP, Hadoop, or on-prem SQL/NoSQL systems).
• Ensure data integrity, governance, and security best practices across pipelines and data lakes/warehouses.
• Troubleshoot and resolve data issues and performance bottlenecks in real-time and batch pipelines.
• Monitor job performance and implement automation and alerting for data operations.
• Contribute to documentation, code reviews, and development best practices.

Skills and attributes for success

• 2–6 years of experience in data engineering or related roles.
• Proficient in SQL, Python, or Scala for data processing.
• Experience with data orchestration tools like Apache Airflow, DBT, or Luigi.
• Familiarity with cloud platforms (AWS Glue, Azure Data Factory, GCP Dataflow, etc.).
• Hands-on experience with data warehouses such as Snowflake, BigQuery, or Redshift.
• Understanding of data modeling, normalization, and data warehousing concepts.
• Exposure to CI/CD, version control (Git), and agile development practices.

To qualify for the role, you must have

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• Knowledge of streaming data frameworks (Kafka, Spark Streaming, Flink) is a plus.
• Experience working in consulting or client-facing environments (for Senior Associate roles).
• Certifications in AWS/Azure/GCP or specific data tools.

Your key responsibilities

• Design, build, and maintain efficient, reusable, and scalable ETL/ELT pipelines for structured and unstructured data.
• Develop and optimize data workflows to support advanced analytics, machine learning models, and reporting tools.
• Collaborate with data scientists, analysts, and business stakeholders to gather requirements and ensure data quality and availability
• Work with cloud and on-prem data platforms (e.g., AWS, Azure, GCP, Hadoop, or on-prem SQL/NoSQL systems).
• Ensure data integrity, governance, and security best practices across pipelines and data lakes/warehouses.
• Troubleshoot and resolve data issues and performance bottlenecks in real-time and batch pipelines.
• Monitor job performance and implement automation and alerting for data operations.
• Contribute to documentation, code reviews, and development best practices.

Skills and attributes for success

• 2–6 years of experience in data engineering or related roles.
• Proficient in SQL, Python, or Scala for data processing.
• Experience with data orchestration tools like Apache Airflow, DBT, or Luigi.
• Familiarity with cloud platforms (AWS Glue, Azure Data Factory, GCP Dataflow, etc.).
• Hands-on experience with data warehouses such as Snowflake, BigQuery, or Redshift.
• Understanding of data modeling, normalization, and data warehousing concepts.
• Exposure to CI/CD, version control (Git), and agile development practices.

To qualify for the role, you must have

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• Knowledge of streaming data frameworks (Kafka, Spark Streaming, Flink) is a plus.
• Experience working in consulting or client-facing environments (for Senior Associate roles).
• Certifications in AWS/Azure/GCP or specific data tools.

What we look for

• Highly motivated individuals with excellent problem-solving skills and the ability to prioritize shifting workloads in a rapidly changing industry.
• An effective communicator, you'll be a confident leader equipped with strong people management skills and a genuine passion to make things happen in a dynamic organization.