We're looking for Data Engineers

Responsibilities:
• Design, build, test, and deploy automated data pipelines and ETL/ELT processes on our Azure and Databricks platform.
• Write clean, maintainable, production-ready code in Python and PySpark for data transformations, integrations, and aggregations.
• Develop, tune, and optimize complex SQL queries to ensure high performance and efficient pipeline execution.
• Ensure end-to-end data quality, consistency, and reliability across all production data flows.
• Data Modeling & Engineering Design (30%)
• Actively contribute to designing and implementing a harmonized relational and analytical data model that serves as the single source of truth for downstream analytics.
• Analyze existing multi-source data models and schemas to understand data flows, entity relationships, constraints, and business logic.
• Collaborate closely with Data Analysts and business stakeholders to translate analytical requirements into robust, scalable data structures.
• Ensure data modeling consistency, best practices, and thorough architectural documentation across data assets.
• Technical Delivery & Vendor Oversight (30%)
• Act as the technical point of contact, SME, and quality gatekeeper for deliverables developed by external vendor engineers.
• Perform structured code reviews and pull request (PR) approvals to ensure compliance with P&G; coding, testing, and security standards.
• Partner with the Product Owner to track delivery milestones, technical trade-offs, and early mitigation of technical debt.
• Promote best engineering practices,



continuous integration/continuous deployment (CI/CD), and shared team standards.

Qualifications:
• Technical Ownership & Guidance: Demonstrated experience conducting code reviews, establishing best practices, and providing technical guidance to junior peers or external vendor developers. Strong communication skills with the ability to articulate technical trade-offs to project stakeholders.
• Data Modeling: Expert-level understanding and hands-on experience with relational data modeling, data warehousing concepts (e.g., star/snowflake schemas), and database design.
• SQL Mastery: Expert-level proficiency in SQL, including writing complex queries, performance tuning, and working with advanced functions across different database systems.
• Python & PySpark: Advanced programming skills in Python for data manipulation (e.g., Pandas) and proven, hands-on experience developing solutions with PySpark in a distributed computing environment.
• Cloud & Big Data: Solid, practical experience with the Azure data stack (e.g., Azure Data Lake Storage, Azure Data Factory, Synapse Analytics) and the Databricks platform.
• Analytical Mindset: Exceptional analytical, problem-solving, and critical-thinking skills with a demonstrated ability to deconstruct complex business and data problems. (Note: Relevant applicants will receive an email requesting additional information as part of the next stage. The application process will be completed directly on the team's designated platform, and all subsequent communication and decisions regarding the opportunity are managed by the respective hiring team.)

📌 Data Engineer (Hyderabad)
🏢 Scoutit
📍 Hyderabad