Software Engineer [Data Engineer - Python, SQL, Snowflake, Cloud, Devops (CI/CD pipeline) AI (Co-pilot usage and prompt engineering/ Gen AI), Docker, Kubernetes]

Job Description We are seeking a skilled Mid-Level Data & Platform Engineer with strong expertise in Python, Snowflake, and SQL, along with foundational knowledge of DevOps, Microsoft Azure, and AI/ML concepts. The ideal candidate will be responsible for designing, developing, and maintaining data pipelines, supporting cloud-based data platforms, and contributing to automation and AI-driven initiatives. Key Responsibilities Data Engineering Design, develop, and maintain scalable ETL/ELT pipelines using Python and SQL Build and optimize data models, transformations, and workflows in Snowflake Develop data ingestion frameworks from various structured and unstructured data sources Monitor and troubleshoot data pipeline failures and performance bottlenecks Ensure data quality, reliability, and governance standards are maintained Snowflake & SQL Develop and optimize complex SQL queries, stored procedures, views, and tasks Implement Snowflake features such as Virtual Warehouses, Streams, Tasks, and Snowpipe Perform query performance tuning and cost optimization Support data warehouse administration and security best practices Cloud & Azure Work with Azure services such as: Azure Data Factory (ADF) Azure Storage Accounts Azure Key Vault Azure Functions (basic) Azure Synapse (basic exposure preferred) Support deployment and management of cloud-native data solutions DevOps & Automation Utilize Git-based source control and branching strategies Support CI/CD pipelines using Azure DevOps or GitHub Actions Create deployment automation scripts and infrastructure configurations Participate in release management and operational support activities AI & Emerging Technologies Understand foundational AI/ML concepts and use cases Work with AI-assisted development tools (GitHub Copilot, Azure AI services, etc.) Support integration of AI-powered features into data platforms Participate in proof-of-concepts involving Generative AI and data analytics Collaboration Collaborate with data engineers, architects, platform teams, and business stakeholders Participate in Agile ceremonies including sprint planning, reviews, and retrospectives Document technical designs, processes, and operational runbooks Qualifications Bachelor's degree in computer science, Information Technology, Engineering, or related field 3-5 years of experience in Data Engineering, Data Warehousing, or Platform Engineering Strong programming skills in Python Strong experience with SQL development and performance tuning Hands-on experience with Snowflake data warehouse Basic understanding of Azure Cloud services Basic knowledge of DevOps principles, CI/CD, and source control Understanding AI/ML fundamentals and Generative AI concepts Experience with Agile/Scrum methodologies Technical Skills Must Have Python SQL Snowflake ETL/ELT Development Data Modeling Git Azure Fundamentals CI/CD Fundamentals Good to Have Azure Data Factory Azure DevOps Terraform Docker (basic) Power BI Databricks Airflow REST APIs Generative AI & Azure OpenAI Services Additional Information Enjoy a flexible and rewarding work environment with peer-to-peer recognition platforms Recharge and revitalize with help of wellness plans made for you and your family Plan your future with financial wellness tools Stay relevant and upskill yourself with career development opportunities Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://nielseniq.com/global/en/info/niqs-ai-safety-policies/ About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion