Snowflake Data Sharing Jobs in Nagpur

Data Engineer Snowflake (5-7 Years) Nagpur Full-Time Location: Nagpur Experience Required: 5-7 years Job Type: Full-Time Open Positions: 3 Job Overview: We are seeking a highly skilled Data Engineer with expertise in Snowflake and ETL processes to join our dynamic team. The successful candidate will help optimize and expand our data pipeline architecture, ensuring efficient data flow for cross-functional teams. This is an exciting opportunity for those who love building scalable data systems from scratch and optimizing existing ones. You will collaborate with software developers, data architects, data analysts, and data scientists to ensure seamless data delivery and contribute to the next generation of our products and data initiatives. Key Responsibilities: Design and optimize data pipelines and architecture for improved data flow and efficiency. Collaborate with software developers, data analysts, and data scientists to support data initiatives. Build and optimize ETL workflows using Snowflake and other technologies. Craft and optimize complex SQL queries and stored procedures for data transformation, aggregation, and analysis. Develop and maintain Snowflake data models, ensuring scalability and optimal performance. Utilize Snowpark for data processing within the Snowflake platform. Integrate Snowflake with AWS S3 for efficient data storage and retrieval. Implement DBT (Data Build Tool) for data modeling and transformation within Snowflake. Work on API integrations, particularly with AWS Lambda, to facilitate data workflows. Utilize Git for version control and collaborative code management. Troubleshoot and resolve data issues to ensure data consistency and quality within the Snowflake ecosystem. Create clear and comprehensive technical documentation for data processing and system designs. Support cross-functional teams by optimizing data systems and architectures for future growth. Required Skills and Qualifications: Proficiency in crafting complex SQL queries and Stored Procedures for data transformation and analysis within the Snowflake platform. Strong experience with Snowflake cloud data warehousing service, including data loading, querying, and administration. Expertise in ETL processes and methodologies, specifically leveraging Snowflake's capabilities. Familiarity with DBT (Data Build Tool) for data transformation and modeling. In-depth knowledge of AWS S3 integration with Snowflake for data storage and retrieval. Expertise in Snowpark for processing data within Snowflake. Experience with API integrations, particularly AWS Lambda, for efficient data workflows. Strong knowledge of Git for version control and collaborative development. Ability to troubleshoot data issues and ensure high data quality and consistency in the Snowflake ecosystem. Excellent documentation skills to create and maintain clear technical documentation. Solid experience with Python for data manipulation and analysis in the Snowflake environment. Experience in creating and maintaining data integration and transformation workflows using DBT. If you're passionate about data architecture, Snowflake, and building scalable, high-performance data systems, apply now for the Data Engineer Snowflake position in Nagpur or Pune!

Data Engineer Big Data Job Location: Nagpur Experience Required: 5 to 7 years Positions Open: 3 Shift: Rotational Shift Job Overview: We are looking for a talented Data Engineer with expertise in Big Data technologies to join our growing team. As a Data Engineer, you will be responsible for expanding and optimizing our data pipeline architecture. You will work closely with software developers, database architects, data analysts, and data scientists to ensure the seamless flow of data across various systems. This role requires proficiency in Hadoop, Hive, Spark, and other big data technologies, as well as solid experience in data transformation and ETL processes. If you are passionate about building and optimizing data systems, this is the role for you! Key Responsibilities: Data Pipeline Architecture: Expand and optimize the architecture for data flow and collection across various teams. Big Data Technologies: Work with Hadoop ecosystem tools such as Hive, Sqoop, and Spark to process large datasets. SQL Optimization: Craft and optimize complex SQL queries for data transformation, aggregation, and analysis. Python Programming: Use Python (including libraries like Pandas and NumPy) to process and manipulate data efficiently. ETL Processes: Ensure smooth data movement and transformation by applying industry best practices in ETL. Data Warehousing: Apply knowledge of data warehousing concepts to optimize data storage and retrieval. Data Quality Management: Troubleshoot data-related issues, ensuring the quality, consistency, and integrity of data. Collaboration: Work closely with cross-functional teams, translating complex technical concepts to non-technical stakeholders. Cloud Integration: Use cloud platforms (e.g., AWS, Azure, GCP) to integrate data systems and services. Automation: Write and maintain shell scripts or other automation tools for efficient data processing. Documentation: Create clear, concise technical documentation to facilitate knowledge sharing and communication across teams. Required Skills and Qualifications: 5 to 7 years of experience in Data Engineering, with a focus on Big Data technologies. Proficiency in SQL for data manipulation and analysis. Strong programming skills in Python (Pandas, NumPy) for data processing and manipulation. Hands-on experience with big data tools such as Hadoop, Hive, Sqoop, and Spark. In-depth understanding of ETL processes and data transformation methodologies. Experience in designing data models and optimizing data storage in data warehouses. Knowledge of cloud platforms (e.g., AWS, Azure, GCP) and their data engineering services is a plus. Ability to write shell scripts or other automation scripts for data processing. Ability to troubleshoot data-related issues and ensure data quality and consistency. Strong collaboration skills in a cross-functional team environment. Ability to communicate complex technical concepts to non-technical stakeholders. Preferred Skills (Good to Have): Experience with Data Lake architecture and integration. Familiarity with Stream Processing and related technologies. Knowledge of Cloud platforms (AWS, Azure, GCP) and their data services. Experience with Big Data frameworks and data modeling.