Senior Data Engineer at NielsenIQ

Pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

17 May, 26

Salary

0.0

Posted On

16 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Pyspark, Python, Scala, Java, SQL, Apache Spark, ETL, Azure Databricks, Snowflake, Apache Airflow, Azure, CI/CD, Github, Infrastructure-as-Code, Data Governance, Performance Optimization

Industry

Software Development

Description

Job Description t's an exciting time to be a builder. Constant technological advances are creating an exciting new world for those who understand the value of data. The mission of NIQ’s Media Division is to turn NIQ into the global leader that transforms how consumer brands plan, activate and measure their media activities. By combining technology and our extensive data assets on consumer purchases, interests, lifestyles, and media we allow advertisers to leverage outcomes to maximize their return on advertising spend. As a data engineer, you'll design and build robust data pipelines and architectures that power these insights. Key Responsibilities: Data Pipeline Development: Design, build, and maintain scalable and reliable ETL pipelines that handle both batch and streaming data sources. Data Lakehouse: Implement and manage solutions to centralize and optimize access to data on our Azure Databricks instances. Data Quality & Integrity: Monitor and ensure the quality, integrity, and availability of data throughout its lifecycle, implementing tools and checks to uphold high data standards. Data Governance & Compliance: Support data governance practices, ensuring data is collected, stored, and accessed in alignment with regulatory requirements and internal policies. Collaboration: Work alongside data scientists, analysts, and business teams to understand data needs, troubleshoot issues, and implement data solutions that align with business objectives. Performance Optimization: Continuously improve data processes and infrastructure, optimizing for speed, cost-efficiency, and scalability. Qualifications Experience: At least 5+ years working as a Data Engineer. Technical Proficiency: Experience with programming languages such as Pyspark, Python, Scala or Java; strong SQL skills; deep experience with big data frameworks such as Apache Spark. ETL & Data Pipelines: Proven experience building and maintaining ETL processes, with deep knowledge and experience with Azure Databricks, Snowflake and Apache Airflow. Cloud Services: Experience with cloud-based data services (Azure), with knowledge of storage, compute, and networking. AI & ML : Basic understanding of AI/ML concepts and ability to collaborate with Data Science team. DevOps and CI/CD: Experience with CI/CD tooling such as Github and Infrastructure-as-Code. Problem-Solving Skills: Ability to troubleshoot data issues and work with stakeholders to address data-related needs and challenges. Communication: Clear, collaborative communicator able to work effectively within cross-functional team 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://www.nielseniq.com/global/en/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

Responsibilities

The role involves designing, building, and maintaining scalable ETL pipelines for both batch and streaming data, and implementing solutions to centralize and optimize data access on Azure Databricks Data Lakehouse instances. Responsibilities also include ensuring data quality, supporting governance, and optimizing data processes for speed and scalability.