Role Description We're looking for an experienced Lead Data Engineer to design, build, and scale modern data platforms while leading a high-performing engineering team. - Design and develop scalable data pipelines and integration solutions. - Build and optimize ETL/ELT processes, data warehouses, lakehouses, and analytics platforms. - Implement data modelling, governance, quality, and performance best practices. - Lead technical delivery, mentor engineers, and establish engineering standards. - Collaborate with business and technical stakeholders to translate requirements into scalable data solutions. - Drive end-to-end delivery of enterprise data projects using Agile methodologies. Qualifications - 8+ years of experience in Data Engineering, Data Warehousing, or Cloud Data Platforms. - 3+ years of technical leadership or team management experience. - Strong experience with Microsoft Fabric, Databricks, Azure SQL/SQL Server, and modern data architectures. - Proficiency in Python, PySpark, SQL, and data orchestration tools such as Azure Data Factory, Fabric Data Factory, or similar. - Experience with DevOps practices, CI/CD pipelines, and version control. - Exposure to Power BI and semantic modelling is advantageous. Requirements - Bachelor's degree in Computer Science, IT, Data Science, Engineering, or a related field. - Relevant cloud or data engineering certifications are advantageous. Key Skills - Data Engineering & Architecture - ETL/ELT Development - Data Modelling & Lakehouse Design - Cloud Analytics Platforms - Technical Leadership & Mentorship - Performance Optimization - Stakeholder Management - Agile Delivery

• Design and implement streaming and batch data pipelines for data integration, ingestion, data quality management (quality gating), transformations, and auditing. • Perform feature engineering and data exploration. • Collaborate with business and operations teams to align on requirements, and to request and standardize waveform/sensor data. • Build and maintain the Gold data layer, key KPIs, and PoC evaluation frameworks. • Set up and maintain solid engineering practices, including CI/CD pipelines, Infrastructure as Code (IaC), version control (Git), unit and integration testing, and proper documentation.

Role Description - Design and govern conceptual, logical, and physical data models for banking domains (Customer, Account, Transaction, Product, Risk, Compliance); experience in data modeling tools like ER Studio. - Define enterprise data architecture standards and modeling best practices aligned with Azure/Snowflake services (ADLS, Azure SQL, Snowflake, etc.). - Experience in mapping data elements from source systems to target systems; experience in FIS Horizon or IBIS is preferable. - Partner with business, data engineering, and platform teams to enable financial reporting solutions. - Proficient in overall Data architecture and design of data components; support Data engineers in the overall development lifecycle. - Support Azure-based data platforms and data products, optimizing models for performance, cost, and future extensibility. - Hands-on experience in SQL and Excel, with strong skills in reverse engineering and developing clear and well-structured documents and presentations. Knowledge of Snowflake is preferable. Qualifications - Experience in data modeling tools like ER Studio. - Knowledge of Azure/Snowflake services (ADLS, Azure SQL, Snowflake, etc.). - Experience in FIS Horizon or IBIS is preferable. - Proficient in SQL and Excel. - Strong skills in reverse engineering and documentation. - Knowledge of Snowflake is preferable. Requirements - Experience in data architecture and design. - Ability to partner with various teams for financial reporting solutions. - Support for Azure-based data platforms and products. Benefits - Inclusive workplace with a focus on individuality and growth. - Commitment to equal employment opportunity (EEO) and affirmative action. Company Description At Zensar, we’re “experience-led everything.” We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. - Part of the $4.8 billion RPG Group. - Community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. - Explore Life at Zensar and join us to Grow. Own. Achieve. Learn.

Role Description We’re looking for a Senior Data Engineer to architect and maintain cutting-edge data systems that power analytics, AI, and operational decision-making. In this role, you’ll take ownership of end-to-end data lifecycles, designing pipelines, models, and architectures that support real-time insights and machine learning at scale. - Design Scalable Data Architecture: Build modern, cloud-native data platforms (AWS, Snowflake, Databricks) supporting batch and streaming use cases. - Develop Efficient Data Pipelines & Models: Automate ETL/ELT workflows, optimise data models, and enable self-serve analytics and AI. - End-to-End Data Ownership: Manage ingestion, storage, processing, and delivery of structured and unstructured data. - Performance & Cost Optimisation: Continuously tune infrastructure for high concurrency, low latency, and cost efficiency. - Real-Time Integration & Analytics: Ingest telemetry, API, and application data in real time to power dashboards and AI-driven tools. - ML & AI Enablement: Provision datasets for ML/AI workloads, integrating with SageMaker, Snowflake ML, and MLOps best practices. - Data Governance & Security: Ensure robust data governance, compliance (GDPR, SOC 2), and enterprise-grade security. - Collaboration & Strategy: Work closely with Product, Engineering, DevOps, and Analytics teams to align data solutions with business goals. Qualifications - Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or related field (Master’s preferred) - Relevant certifications (AWS Certified Data Analytics, Solutions Architect, SnowPro Core) Requirements - Significant experience in technology roles, with 5+ years in data engineering on real-time, scalable cloud platforms (AWS & Snowflake preferred). - Experience in SaaS/product companies managing large-scale IoT, telemetry, or digital datasets is highly desirable. - Technical Expertise: - AWS (S3, Glue, Lambda, Athena, Kinesis) - Snowflake (data pipelines, schema design, query optimization) - Data modeling, ETL/ELT, real-time streaming (Kafka, Kinesis) - Big data processing (Spark, Airflow), SQL, Python, Java/Scala - BI & analytics platforms (Tableau, Looker) - ML/AI integration (SageMaker, TensorFlow, Snowflake ML, feature stores) - Data governance, security, and compliance frameworks - Attributes: Strong communicator, collaborative, analytical, and strategic. Ability to balance multiple projects while driving innovation and operational excellence. Benefits - Competitive compensation - A base salary that reflects your expertise and impact. - Bonus scheme to share in our success. - Flexibility & work-life balance - Remote working arrangements to support your lifestyle. - An open holiday policy with no upper limit—take the time you need, when you need it. - Support for volunteering and causes that matter to you. - Growth & development - Opportunities for professional development and career progression. - Exposure and interaction with global teams. - Inclusive, supportive culture - A commitment to diversity, equity, and inclusion. - A collaborative environment where your voice is valued and your wellbeing is prioritised. - Impact & purpose - The chance to work on technology that drives global economic inclusion and makes a real difference in people’s lives.