Data Engineer

About ADM: We are one of the world’s largest nutrition companies and a global leader in human and animal nutrition. We unlock the power of nature to provide nourishing quality of life by transforming crops into ingredients and solutions for foods, beverages, supplements, livestock, aquaculture, and pets. About ADM India Hub: At ADM, we have long recognized the strength and potential of India’s talent pool, which is why we have maintained a presence in the country for more than 25 years. Building on this foundation, we have now established ADM India Hub, our first GCC in India. At ADM India Hub, we are hiring for IT and finance roles across diverse technology and business functions. We stand at the intersection of global expertise and local excellence, enabling us to drive innovation and support our larger purpose of unlocking the power of nature to enrich quality of life. Job Title: Data Engineer II We are seeking a skilled and motivated Power BI developer to join our dynamic ADM team with 5 plus years of experience. should highlight responsibilities like developing interactive dashboards, creating reports, integrating data from diverse sources, and collaborating with stakeholders to gather requirements and deliver solutions. Key skills to include are experience with DAX, SQL, ETL processes, Databricks and a proven ability to translate business needs into data visualizations. Key responsibilities will typically involve a mix of data preparation within Databricks and data visualization in Power BI: Developed interactive Power BI reports and dashboards to visualize key business metrics, enabling data-driven decision-making and improving efficiency. Engineered complex data models within Power BI Desktop, integrating and transforming data from multiple sources including SQL Server, Excel, and Azure services. Implemented advanced Data Analysis Expressions (DAX) formulas and M Query for custom calculations, measures, and calculated columns to meet specific business requirements. Optimized existing Power BI reports and dashboards for performance and scalability, reducing load times through query and data model optimization techniques. Designed and implemented Row-Level Security (RLS) within Power BI to ensure data governance and compliance with data privacy regulations. Streamlined ETL processes using SSIS and SQL for data extraction, transformation, and loading into the data warehouse, enhancing data loading speed. Published and managed reports and dashboards on the Power BI Service, administering user access, workspaces, and scheduled data refreshes. Troubleshot and resolved issues related to data integration, report accessibility, and performance bottlenecks, ensuring seamless data flow and user experience. Provided training and support to end-users on Power BI functionalities, increasing user adoption and self-service analytics capabilities. Power BI: Power BI Desktop, Power BI Service, Power Query, Power Pivot, DAX, M Query, Custom Visuals, Performance Tuning. Databases & ETL: SQL, T-SQL, SSIS, SSAS, SSRS, Data Warehousing, Data Modeling (Star/Snowflake Schema), ETL Processes, Azure SQL Database. Programming & Other Tools: Python, R, JavaScript (optional), Excel (Advanced), SharePoint, Azure Data Factory, Git, Agile methodologies. Developed and implemented advanced time intelligence DAX functions (DATEADD, SAMEPERIODLASTYEAR) to calculate Year-over-Year (YoY) growth and rolling averages, providing deeper trend analysis". Engineered dynamic ranking measures using RANKX and ALLSELECTED to identify top 10 regional sales performers, enabling targeted performance reviews. Used CALCULATE and iterator functions to define custom, context-sensitive KPIs for finance, resulting in more accurate financial and operational insights Data Sourcing and Connection: Connect Power BI Desktop to Databricks using the native connector, specifically leveraging Databricks SQL warehouses for optimized performance. Write and optimize native SQL queries in Power BI's Advanced Editor to pull data efficiently from the Databricks lakehouse, reducing data load times. Data Modeling & Transformation: Collaborate with data engineers to ensure data models in Power BI align with the medallion architecture (connecting primarily to the "Gold" layer) for clean, business-ready data, minimizing extensive transformations within Power Query. Data Governance & Security: Implement and manage security protocols, such as Row-Level Security (RLS) in Power BI and integrating with Databricks' Unity Catalog for seamless authentication (e.g., Automation & Orchestration: Use Databricks Workflows and Jobs to automate the refreshing and updating of Power BI semantic models when the underlying data changes, ensuring data freshness. Performance Tuning: Optimize Power BI report performance by leveraging DirectQuery or a composite model approach against large Databricks datasets, analyzing query performance, and addressing bottlenecks. Collaboration: Work closely with data engineers and data scientists to understand data pipelines and source systems, translating complex business requirements into robust BI solutions