Senior Big Data Engineer II

MetLife; Dadri; On-site; INR 1,200,000 - 1,600,000; Full time

Job summary

MetLife is seeking a Data Engineer to play a critical role in the data and analytics life cycle. The role requires 10-12+ years of experience with Big Data, Engineering and Cloud expertise.

You will design and maintain ETL/ELT pipelines on Azure or on-prem, ensuring data quality and governance while leading and mentoring analytics talent. Responsibilities include building robust pipelines, optimizing performance, collaborating with multiple partners, and driving solution design and estimation.

Qualifications

• 10-12+ years of relevant experience in data engineering and analytics.
• Design, build, and maintain robust ETL/ELT pipelines on cloud (Azure) or on-prem.
• Experience with big data frameworks (Spark, Hadoop, Hive) and data platforms.
• Strong data quality, security, and compliance awareness.
• Ability to lead design, solutioning and estimation, and coach teams.

Responsibilities

• Design, build, and maintain ETL/ELT pipelines for batch and real-time processing.
• Monitor, optimize, and troubleshoot data pipelines for reliability and performance.
• Collaborate with business, technology, and governance teams.
• Lead data architecture discussions and drive estimation efforts.
• Provide people leadership and mentorship to analytics talent.
• Work with data warehouses, data marts, and data lakes.
• Utilize Azure data factory, Databricks, Synapse, and related services.
• Ensure data processing, governance and security standards are followed.
• Hands-on coding in SQL and Python/Scala; manage distributed databases.
• Enable real-time and streaming pipelines with Spark.

Skills

SQL

Python/Scala

NoSQL

Azure

Spark

Hadoop

Hive

Azure Data Factory

Databricks

Cosmos DB

Data Warehouses

Data Lakes

CI/CD

Git

Unix Shell Scripting

MongoDB

NiFi

Education

Bachelor's degree in computer science / information technology or equivalent

Tools

Git

Azure DevOps

CI/CD pipelines

Unix shell scripting

MongoDB

NiFi

Job description

GG11.2Data Engineer plays a critical role in data and analytics life cycle and significantly contributes to production grade data and analytics solutions. The role requires one to demonstrate Big Data, Engineering and Cloud expertise. Besides contributing in individual capacity to solve wide ranging business problems, this role also leads and develops Data and Analytics talent10-12+ years of relevant experienceBachelors degree in computer science, information technology or equivalent educational qualification

• Design, build, and maintain robust ETL/ELT pipelines on cloud(Azure) or on-prem to collect, ingest and store large volumes of structured and unstructured data for batch/real time processing
• Monitor, optimize, and troubleshoot data pipelines to ensure reliability, scalability, and performance
• Ensure data processing, quality, security, and compliance guidelines, policies and standards are followed
• Collaborate with multiple partners from Business, Technology, Operations and D&A capabilities (Data Governance, Data Quality, Data Modeling, Data Architecture, Data science, DevOps, BI & insights)
• Independently lead design, solutioning & estimations
• Provide people leadership: coach, develop and engage talent
• SQL, Python/Scala
• NoSql and distributed databases (Hbase, Cosmos DB)
• ETL pipleine design and development; Solutioning and estimation
• Big Data Frameworks : Apache Spark, Hadoop, Hive
• Cloud platforms: Azure data factory, Eventhub, Azure functions, Synapse, Databricks
• Datawarehouses, data marts, data lakes
• Medallion architecture
• Performance tuning, optimization, and data quality validation
• Real-time and batch data processing , streaming pieplines with Spark
• Communication skills, analytical skills, structured problem-solving skills,mentorship & people leadership skills
• Storytelling skills , Partner & Stakeholder engagement experience
• People leadership: talent development & engagement experience
• DevOps practices: Git, AzureDevops, CI/CD pipelines
• Unix shell scripting, MongoDB, Nifi
• Exposure to Gen AI technology and tools
• Banking Financial Services and Insurance domain knowledge