Data Validation Engineer

Role : Data validation Engineer Location : JP Nagar ,Bangalore. Work from office. Face to face interview one round only.

Job Description : Are you someone looking for a challenge to work in a startup environment and innovate in a global environment to help build a SaaS Service to scale? Are you willing to roll up your sleeves and do what it takes to deliver value to Customers? As we expand our Engineering operations in India, we are looking for a Sr. Data Engineer to join us and help build robust data pipelines that is an integral part of our SaaS platform The role would offer an opportunity to work with cross functional teams in developing and evolving Cloud services powering innovative technology solutions used in the real estate industry. We are seeking a skilled and experienced Data Engineer to join our dynamic team. The Data Engineer will be responsible for designing, implementing, and maintaining our data infrastructure, pipelines, and systems. This role involves collaborating with cross-functional teams to ensure efficient data flow, data quality, and optimal performance. The ideal candidate should have a strong background in software engineering, database management, and data architecture, along with proficiency in relevant technologies and tools. Responsibilities : Lead the design and implementation of robust data pipelines for efficient extraction, transformation, and loading (ETL) of large datasets from diverse sources. Collaborate with stakeholders to understand business requirements, translating them into scalable data solutions tailored to end-user needs. Enhance and maintain our data architecture, ensuring scalability, reliability, and performance. Investigate and resolve data anomalies within ETL pipelines, ensuring data integrity and accuracy. Develop and maintain documentation for data processes, ensuring clarity and sustainability. Utilize AWS platform capabilities to architect and operate scalable production solutions. Implement data security practices and compliance measures to protect sensitive information. Build and manage data warehouses and data lakes to store and organize large datasets. Implement data quality checks and procedures to ensure data accuracy and consistency. Automate data workflows and processes using scripting languages and data pipeline orchestration tools. Collaborate with business analysts, onboarding teams, and business stakeholders to understand data needs and translate them into technical solutions. Monitor and troubleshoot data pipelines, identify bottlenecks, and optimize performance of data infrastructure to ensure scalability and efficiency. Troubleshoot issues with production data and / or inconsistencies and propose sustainable solutions to address them Document data pipelines and processes for maintainability and knowledge sharing. Stay updated with emerging technologies and best practices in data engineering, and propose innovative solutions. Document system architectures, processes, and procedures for knowledge sharing and future reference. Provide technical guidance and support to junior team members, and contribute to their professional development Skills and Qualifications : 1) Strong proficiency in SQL with hands-on experience in relational databases such as MySQL and Oracle, including the development and maintenance of stored procedures. 2) Experience with data validation, data quality testing, and frameworks for automated and manual data validation processes. 3) Solid understanding of data modeling concepts and their application in building scalable and reliable data pipelines. 4) Design and implement data validation processes and data quality checks to ensure the accuracy, completeness, and consistency of critical datasets. 5) Collaborate with cross-functional teams (e.g., data engineering, product, analytics) to define and execute data validation strategies aligned with business requirements. 6) Analyze data validation results and troubleshoot issues to determine root causes and implement corrective actions. 7) Experience with scripting languages like Python for data validation or test automation 8) Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent experience). 9) A minimum of 5 years of experience as a Data Engineer or similar role. 10) Strong proficiency in SQL and experience with relational databases (e.g., MySQL, PostgreSQL). 11) Excellent problem-solving and analytical skills. 12) Strong communication and collaboration skills. 13) Ability to work independently and as part of a team.