IC Senior_Data Engineer_Sr. Software Engineer_155 (PySpark, Airflow)
Ugam, a Merkle company, is a leading analytics and technology services company. Our customer-centric approach delivers impactful business results for large corporations by leveraging data, technology, and expertise. We consistently deliver superior, impactful results through the right blend of human intelligence and AI. With 4600+ people spread across locations worldwide, we successfully deploy our services to create success stories across industries like Retail & Consumer Brands, High Tech, BFSI, Distribution, and Market Research & Consulting. Over the past 21 years, Ugam has been recognized by several firms including Forrester and Gartner, named the No.1 data science company in India by Analytics Insight, and certified as a Great Place to Work®.
The name Ugam comes from the ancient Sanskrit language and means “source” or “origin.” Ugam seeks to be the source of solutions for the complex problems of retailers, brands and market research firms worldwide. The name signifies the company’s position as a pioneer in the market for data and analytics, and the source of relevant actionable insights for clients.
Ugam, a Merkle company and part Dentsu, is looking for Senior Software Engineer (Data Engineer).
This role is responsible to architect, develop and optimize petabyte scale data transformations pipelines and data platforms with smart fault tolerance and monitoring capabilities. You will design strategies to integrate ML models within the data flows using state-of-the art GCP environments such as Composer, Dataproc, BiqQuery, BQML, VertexAI etc.
The ideal candidate will develop production quality python, pyspark and Ariflow code and mentor teams members. S/he will talk to business, participate in solution design, and build standards and best practices to address short- and long-term needs of the business (documentations, frameworks, boilerplate abstractions etc.)
Role: Senior Software Engineer (Data Engineer)
- Build pipelines to manage audience data for personalised marketing campaigns, integrate audience data from various sources to build one view of the customer
- Perform experimentation at scale by tagging audiences based on complex hierarchy of customer, product, and regional factors
- Responsible for development of the workflow orchestration & ETL pipelines within marketing's analytics and data science platforms. You will ensure that the data pipeline infrastructure meets the analysis, reporting, and data science needs of the marketing organization.
- Implement continued design, development and optimization of the marketing data pipelines & data prep infrastructure built on cutting-edge cloud technologies.
- Embrace an active team role to help design, implement, and launch efficient and reliable data pipelines moving data across several platforms including Data Warehouse, online caches, and real-time systems.
- Create data architecture that is flexible, scalable, and consistent for cross-functional use, and aligned to stakeholder business requirements.
- Deploy workflow orchestration and demonstrate expertise in data modeling, ETL development, and data warehousing
- Validate Data Engineering business data elements, organizational and business intelligence architecture designs for engineering functional areas from Dashboards, Data Lakes, Data Operations, ML - AI, and upstream/downstream intake and output processes
- BA/BS Degree in Computer Science, any Engineering discipline, Statistics, Information Systems or another quantitative field.
- 5+ years of industry experience in data engineering, data science, or related field with a track record of manipulating, processing, and extracting value from large datasets
- Work experience with developers and business areas to design, configure, deploy, and maintain custom ETL Infrastructure to support project initiatives
- Experience in interacting with multiple teams, client stakeholders and able to fix the issues in a shorter span of time
- Experience building and managing data pipelines and repositories in cloud environments such as Google Cloud, Microsoft Azure or AWS
- Experience in Airflow is a must
- Experience extracting/cleansing data and generating insights from large transactional data sets using Spark SQL, SQL, Python, and PySpark on cloud
- Experience with optimizing Spark pipelines on Dataproc, Databricks or similar technologies.
- Must have exceptional and effective communication, organization, and time management skills
- Must be pro-active and determined (Initiates action, Analytical and problem solver)
All your information will be kept confidential according to EEO guidelines.