Job location is Pune Hinjewadi. Monday to Friday Work from office. About company : leading provider of data management and analytics solutions, offering an AI-powered platform designed to help organizations efficiently manage, integrate, and analyze their data. Our comprehensive suite of tools includes robust data management capabilities, a powerful business rule engine, and advanced analytics features. By leveraging its platform, organizations can enhance their data-driven decision-making processes, improve operational efficiency, and drive business value through better insights and innovation. Headquarters - New York, New York Founded in 201 Specialties - data management, analytics, artificial intelligence, predictive analytics, machine learning, enterprise platform, financial services, banking, and insurance. Job Title: Senior Data Engineer Location: Pune Job Type: Full-Time Reports To: Data Engineering Manager / Director of Data Engineering Key Responsibilities: Data Architecture & Design: Develop and maintain scalable and efficient data pipelines to process large datasets. ETL Processes: Design, implement, and optimize ETL processes using modern tools and frameworks. Data Integration: Integrate data from various sources into a centralized data warehouse or data lake, ensuring data quality, security, and governance. Cloud Platforms: Design and implement data solutions on cloud platforms such as AWS, Azure, or GCP. Optimization: Identify and resolve performance bottlenecks in data processing and queries. Collaboration: Work closely with data scientists, analysts, and business teams to understand data requirements and deliver actionable insights. Tool Proficiency: Leverage Databricks or Snowflake for data management, transformation, and analytics. Mentorship: Provide technical leadership and mentorship to junior data engineers. Documentation: Maintain clear documentation for data processes, architectures, and systems. Required Skills & Qualifications: Experience: Minimum of 5 years of experience in data engineering or a related field, with a proven track record of building robust data pipelines. Data Warehousing & ETL: Strong knowledge of data warehousing concepts and experience with ETL tools such as Apache Airflow, Talend, or custom Python-based pipelines . Cloud Platforms: Hands-on experience with cloud technologies (AWS, Azure, or GCP) for data engineering and management. Databricks or Snowflake: Expertise in one of the following: Databricks: Experience with Spark, Delta Lake, and managing big data workloads. Snowflake: Proficiency in using Snowflake for data warehousing, data integration, and analytics. Programming Skills: Proficient in Python, SQL, and other data engineering languages (e.g., Java, Scala). Data Modeling: Experience in designing and implementing complex data models for large-scale applications. Data Governance & Quality: Knowledge of data governance best practices, including ensuring data quality, security, and compliance . Collaboration & Communication: Excellent communication skills, both technical and non-technical, to collaborate with cross-functional teams. Preferred Qualifications: Experience with containerization (Docker, Kubernetes). Familiarity with machine learning workflows or AI pipelines. Strong understanding of DevOps principles for continuous integration and deployment (CI/CD). Benefits: Competitive salary and performance-based bonuses Health, dental, and vision insurance 401(k) plan with company match Flexible work hours and remote work options Career growth opportunities and professional development support
