Data Engineer – Specialist

Data Engineer - Specialist Location: Bangalore, India Full/ Part-time: Full time About Carrier     Carrier Global Corporation, global leader in intelligent climate and energy solutions, is committed to creating innovations that bring comfort,   safety   and sustainability to life. Through   cutting-edge   advancements in climate solutions such as temperature control, air   quality   and transportation, we improve lives, empower critical   industries   and ensure safe transport of food, life-saving medicines and more. Since inventing modern air conditioning in 1902, we lead with purpose: enhancing the lives we live and the world we share. We continue to lead because of our world-class, inclusive workforce that puts the customer at the   center   of   everything we do. For more information, visit   corporate.carrier.com   or follow Carrier on social media at @Carrier.

The Data Engineer is a highly technical, hands-on senior individual contributor responsible for building scalable, enterprise-grade data pipelines and reusable data products across Snowflake, AWS, and GCP platforms. The role demands advanced skills in SQL and Python, hands-on data modelling, and experience with data governance tools such as Ataccama and Atlan. The engineer will actively build, optimise, debug, and manage production-scale data pipelines, integrating over 70 ERP systems (SAP ECC, Atlas, JDE, Baan, etc.). The ideal candidate is passionate about deep data engagement, solving complex modelling problems, and writing high-performance code at scale.

Data Engineering & Pipeline Development Design and build scalable ingestion, transformation, and serving pipelines. Develop highly optimised, advanced SQL transformations (heavy daily usage). Build Python-based data processing frameworks and reusable components. Work extensively across Snowflake, AWS, and GCP ecosystems. Handle ingestion and harmonisation from 70+ ERP systems. Optimise large-scale joins, aggregations, and complex transformation logic. Ensure performance, scalability, and cost efficiency. Advanced Data Modelling Design and implement conceptual, logical, and physical data models. Build enterprise-grade master data and finance data models. Develop reusable, consumption-ready datasets. Apply dimensional modelling and modern data platform patterns. Align models with data product and enterprise architecture principles. Optimise modelling decisions for performance in Snowflake and cloud platforms. This role requires hands-on modelling — not just conceptual knowledge. Technical Ownership & Deep Engineering Own end-to-end development lifecycle of pipelines and models. Perform coding, debugging, refactoring, and optimisation. Address complex data inconsistencies across fragmented ERP systems. Write production-grade, maintainable SQL and Python code. Actively troubleshoot performance bottlenecks and transformation issues. Data Quality, Governance & Metadata Implement and manage data quality rules using Ataccama (required experience). Work with Atlan or similar data catalog/governance tools (required). Ensure lineage, metadata documentation, and governance standards. Embed validation, monitoring, and observability into pipelines. Support enterprise data standardisation initiatives. Business Collaboration & Requirement Translation Partner with Finance and Corporate stakeholders. Understand KPIs, business definitions, and data nuances. Translate business logic into scalable SQL transformations and models. Challenge ambiguous requirements using data reasoning. Engineering Excellence & Platform Collaboration Work closely with Tech Leads, architects, and platform teams. Follow CI/CD, DevOps, and Infrastructure-as-Code practices. Adopt framework-first and reusable design principles. Continuously improve data product quality and engineering standards.

7–12 years of strong data engineering experience. Advanced SQL