Data Engineer (Spark with Scala/ Python and Azure Databricks and Airflow) at NielsenIQ

Pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

03 Jun, 26

Salary

0.0

Posted On

05 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Spark, Scala, Python, Pyspark, Databricks, Airflow, SQL, Docker, Kubernetes, Azure, Data Warehousing, CI/CD, DevSecOps, Performance Optimization, Memory Utilization

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. For more information, visit NIQ.com. Job Description As a Data Engineer, you’ll be part of a team which works with cutting-edge technologies such as Spark, (Scala & Pyspark), python, Databricks, Airflow, SQL, Docker, Kubernetes, and other Data engineering tools. Responsible to maintianing & assembling data pipelines that consume large datasets, runs the complex data transformations that are needed to generate the facts for the clients. Responsible for integrating finished models into the pipelines that also helps in building the insights for the customer. Use your spark skills to optimize spark code (including data science models). Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using Azure, Databricks and SQL technologies Write and maintain documentation for features you work on & transition them to L2 support. Qualifications Minimum 2-4 year of experience as Data engineer Experience modeling or manipulating large amounts of data is a must. Proven experience working as a data engineer Highly proficient in using the spark framework (python and/or Scala) Extensive knowledge of Data Warehousing concepts, strategies, methodologies. Programming experience in Python, SQL, Scala Direct experience of building data pipelines using Apache Spark (preferably in Databricks), Airflow. Hands on experience designing and delivering solutions using Azure including Azure Storage, Azure SQL Data Warehouse, Azure Data Lake Experience with CI/CD & DevSecOps is a plus. Experience with Demographic, Retail business is a plus Databricks & Azure Big Data Architecture Certification would be plus Must be team oriented with strong collaboration, prioritization, and adaptability skills required Ability to write highly efficient code in terms of performance / memory utilization 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 maintaining and assembling data pipelines that process large datasets and execute complex data transformations necessary to generate client facts. Responsibilities also include integrating finished models into pipelines to aid in customer insight generation and optimizing Spark code.