Associate Big Data Engineer
Metlife
This job at a glance
- Who can apply
- Freshers and up to 3 years · Bachelor's degree
- Must know
- OperationsAzureETLPythonSQLSpark
- Nice to have
- Stakeholder managementMachine learningLLMs
- Work
- On-site in Pune
- Pay
- Not stated by the employer.
- Listed
- 29 Oct 2026 · still open
Sign in free to see which of these skills your resume already shows.
About the Role
The Associate Big Data Engineer is responsible for designing, developing, and maintaining scalable data engineering solutions that enable trusted data, advanced analytics, and actionable business insights across MetLife's global operations. This role contributes to MetLife's Data & Analytics vision by supporting the collection, processing, storage, and delivery of structured and unstructured data across cloud and on-premise environments. This position offers an opportunity to work with modern big data technologies, cloud platforms, and enterprise-scale analytics ecosystems. The role provides exposure to end-to-end data engineering practices, collaboration with global teams, and opportunities to contribute to innovative data and AI-driven initiatives that create measurable business value.
Key Responsibilities
- Design, build, and maintain robust ETL/ELT data pipelines on Azure cloud and on-premises platforms for large-scale data ingestion and processing.
- Develop scalable data engineering solutions using technologies such as Apache Spark, Hadoop, Hive, Python, and SQL.
- Ensure data quality, security, governance, and compliance standards are consistently followed throughout the data lifecycle.
- Collaborate with business stakeholders, technology teams, operations teams, and Data & Analytics functions to deliver reliable data solutions.
- Support batch and real-time data processing requirements using cloud-native services including Azure Data Factory, Event Hub, Azure Functions, Databricks, and Synapse Analytics.
- Contribute to data warehouse, data mart, and data lake initiatives to enable enterprise reporting, analytics, and data science solutions.
Requirements & Tech Stack
- Proficiency in SQL and programming languages such as Python or Scala.
- Experience with ETL/ELT pipeline development and data integration processes.
- Knowledge of Big Data technologies including Apache Spark, Hadoop, and Hive.
- Familiarity with Azure cloud services such as Azure Data Factory, Databricks, Synapse Analytics, Event Hub, and Azure Functions.
- Understanding of NoSQL and distributed databases such as HBase and Cosmos DB.
Qualifications
- Bachelors degree in Computer Science, Information Technology, Engineering, or a related discipline.
- 0-3 years of experience in Data Engineering, Big Data, Data Analytics, or related technology domains.
- Strong analytical, problem-solving, and communication skills.
- Ability to work effectively in a collaborative and fast-paced team environment.
Preferred Qualifications:
- Exposure to GenAI technologies, AI-powered development tools, or machine learning concepts.
- Knowledge of data warehouses, data marts, and data lake architectures.
- Understanding of data governance, data quality, and data modeling principles.
- Experience working in cloud-based data engineering environments.
- Demonstrated curiosity, learning agility, and a passion for emerging technologies and innovation.
- Strong stakeholder management and cross-functional collaboration skills.