Senior Software Engineer (Python, Pyspark, Databricks, AWS, SQL) at NielsenIQ

Pune City, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

19 Aug, 26

Salary

0.0

Posted On

21 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Pyspark, Databricks, AWS, SQL, Apache Airflow, AWS Glue, AWS EMR, AWS Lambda, ETL/ELT, Data Pipeline Design, Machine Learning Productionisation, S3, Distributed Data Processing, Data Warehousing, Feature Engineering

Industry

Software Development

Description

Company Description 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. Job Description Engineers in this role build and operate scalable data pipelines on an AWS‑based data platform, working closely with data science teams to productionise models. They support multi‑region operations, troubleshoot production issues, and act as a technical bridge between data science, engineering, and regional operations teams. Strong experience in data engineering, designing and operating large‑scale data pipelines in cloud environments Hands‑on experience with an AWS‑based data platform, including services such as S3, Glue, Spark, EMR/Lambda, and Airflow Proficiency in Python for data processing, orchestration, and automation in production systems Solid understanding of data science and modelling concepts, enabling effective collaboration with data scientists and support for model development and deployment Experience productionising data science models, including upstream data preparation and downstream integration Working knowledge of data ingestion and transfer patterns, including batch, file‑based, API‑based, and streaming approaches Experience with data warehousing and analytical data stores, including schema design, ETL/ELT patterns, and performance optimisation Strong diagnostic and troubleshooting skills across data pipelines, models, and downstream production impacts Experience supporting production data systems, including monitoring, incident resolution, and continuous operational improvement Ability to learn, adopt, and contribute to an in‑house data science framework (InMedia), following defined standards and best practices Proven ability to work effectively across multiple regions and time zones Clear and professional communication skills, translating complex technical issues into actionable insights for engineering, data science, and operations stakeholders Qualifications 6-9 years of hands‑on experience in data engineering, with a proven track record of designing, building, and operating large‑scale, cloud‑based data pipelines. Deep expertise in AWS‑based data platforms, including: S3, Glue, EMR, Lambda, Spark, and orchestration tools such as Airflow. Strong proficiency in Python, focusing on: Data processing Workflow orchestration Automation in production‑grade systems Solid understanding of distributed data processing, data optimisation, and scalable ETL/ELT patterns. Data Science & Model Productionisation Strong exposure to data science workflows, enabling effective collaboration with data scientists throughout the model development lifecycle. Proven experience productionising machine‑learning models: Upstream: Feature engineering, input data preparation, data validation Downstream: Real‑time/batch model integration, scoring pipelines, post‑processing Hands‑on experience supporting model deployment, monitoring, and troubleshooting model‑related production issues. Additional Information 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 Career Site Team: Technology

Responsibilities

Build and operate scalable data pipelines on an AWS-based platform to productionise data science models. Act as a technical bridge between data science, engineering, and regional operations teams to support multi-region operations.