MediaRadar, An Industry Leader in Marketing Intelligence now including the data and capabilities of Vivvix, powers the mission-critical marketing and sales decisions that drive competitive advantage. Our next-generation marketing intelligence platform enables clients to achieve peak performance with always-on insights that span the media, creative, and business strategies of 5 million brands across 30+ media channels and 275 billion in media spend. By bringing the advertising past, present, and future into focus, our clients rapidly act on the competitive moves and emerging advertising trends impacting their business. About the Role We are looking for an experienced and strategic Senior Data Engineer to join our data team. In this role, you will be responsible for building and maintaining scalable, high-performance data solutions using Azure Databricks, Apache Spark, AKS, Airflow, Postgres, and modern data lakehouse architectures. You’ll play a key role in the full software development lifecycle—from design and implementation to deployment and documentation—while collaborating cross-functionally to support analytics, reporting, and operational data needs. This is an exciting opportunity to work along with a great team of data engineers, demanding technologies and an engaging work environment to help shape our data engineering best practices.

• design and maintain data pipelines of real-time and batch • create data strategy, data architecture, and best practices • lead the organization in strategic improvements in data engineering solutions • handle critical applications influencing management decision-making and regulatory reporting

At Mindera, we believe that software is built by people, for people with high performance systems that impact users worldwide. We are looking for a Senior Data Engineer to join an agile, collaborative team where your voice matters as much as your code. You won’t just be managing infrastructure, you’ll be a technical partner helping us build resilient systems that scale. We value empathy, self-organization, and the courage to take risks. If you love solving complex problems and believe that teaching others is the best way to learn, you’ll feel right at home here. We’re looking for someone who loves to build, learn, and guide others. You’ll be working closely with our leadership (CEO/COO) and our clients, so clear communication and a collaborative spirit are key. National and international expected traveling time varies according to project/client and organizational needs: 0%-15% estimated. 💪 How You’ll Contribute - Build & Maintain Pipelines: Design, build, and operate end-to-end data solutions , including both real-time and batch data pipelines. Ensure data flows correctly across architectures, from raw ingestion to modeling-ready layers. - Cross-Cloud Engineering: Leverage expertise across multiple cloud environments to build robust data ecosystems, whether utilizing AWS (S3 and core cloud services) , GCP (BigQuery and Google Cloud Storage) , or Azure (Databricks). - Automate & Orchestrate: Use deep knowledge of Apache Airflow for scheduling, orchestrating, and monitoring workflows. Build software services and automate processes using strong Python development skills. - Advanced Data Modeling: Apply the correct methodologies (Kimball, Inmon, Data Vault) to design Star Schemas, Semantic Models, and highly optimized platforms.

Description and Requirements GG10.2 Data 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.It is an individual contributor role, expected to independently function 5-8+ years of relevant experience Bachelors 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) • SQL, Python/Scala• NoSql and distributed databases (Hbase, Cosmos DB)• ETL pipleine development• 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.,• Partner, Stakeholder engagement experience • DevOps practices: Git, AzureDevops, CI/CD pipelines• Unix shell scripting, MongoDB, Nifi• Exposure to Gen AI technology and tools About MetLife Recognized on Fortune magazine's list of the "World's Most Admired Companies" and Fortune World's 25 Best Workplaces™, MetLife, through its subsidiaries and affiliates, is one of the world's leading financial services companies; providing insurance, annuities, employee benefits and asset management to individual and institutional customers. With operations in more than 40 markets, we hold leading positions in the United States, Latin America, Asia, Europe, and the Middle East. Our purpose is simple - to help our colleagues, customers, communities, and the world at large create a more confident future. United by purpose and guided by our core values - Win Together, Do the Right Thing, Deliver Impact Over Activity, and Think Ahead - we're inspired to transform the next century in financial services. At MetLife, it's #AllTogetherPossible . Join us! #BI-Hybrid