Senior Data Engineer

Senior Data Engineer
This role is a Hybrid work model

Location:

Mumbai (Jogeshwari)

Shift: 12 pm - 8 pm (IST)

Come work on fantastically high-scale systems with us! Blis is an award-winning, global leader and technology innovator in big data analytics and advertising. We help brands such as McDonald's, Samsung, and Mercedes-Benz to understand and effectively reach their best audiences

In doing this, we are industry champions in our commitment to the ethical use of data and believe people should have control over their data and privacy. With offices across four continents, we are a truly international company with a global culture and scale.
We are looking for solid and experienced Data Engineers to work on building out secure, automated, scalable pipelines on GCP. We receive over 350gb of data an hour and respond to 400,000 decision requests each second, with petabytes of analytical data to work with.

We tackle challenges across almost every major discipline of data science, including classification, clustering, optimisation, and data mining. You will be responsible for building stable production level pipelines, maximising the efficiency of cloud compute to ensure that data is properly enabled for operational and scientific causes.

As of March 2025, Blis was acquired by T-Mobile and is now part of T-Mobile Advertising Solutions. This is a growing team with big responsibilities and exciting challenges ahead of it, as we look to reach the next 10x level of scale and intelligence.

At Blis, Data Engineers are a combination of software engineers, cloud engineers, and data processing engineers. They actively design and build production pipeline code, typically in Python, whilst having practical experience in ensuring, policing, and measuring for good data governance, quality, and efficient consumption. To run an efficient landscape we are ideally looking for candidates that are comfortable with event- driven automation across also aspects of our operational pipelines.

As a Blis data engineer, we seek to understand the data and problem definition and find efficient solutions, so critical thinking is a key component to efficient pipelines and effective reuse, this must include defining the pipelines for the correct controls and recovery points not only function and scale. Across the team, everyone supports each other through mentoring, brainstorming, and pairing up.

They have a passion for delivering products that delight and astound our customers and that have a long-lasting impact on the business. They do this while also optimising themselves and the team for long-lasting agility, which is often synonymous with practicing Good Engineering. They are almost always adherents of Lean Development and work well in environments with significant amounts of freedom and ambitious goals

Key responsibilities
Design, build, monitor, and support large scale data processing pipelines.
Support, mentor, and pair with other members of the team to advance our team’s capabilities and capacity.
Help Blis explore and exploit new data streams to innovative and support commercial and technical growth
Work closely with Product and be comfortable with taking, making and delivering against fast paced decisions to delight our customers. This ideal candidate will be comfortable with fast feature delivery with a robust engineered follow up.

Skills and requirements
8+ years direct experience delivering robust performant data pipelines within the constraints of direct SLA’s and commercial financial footprints.
Proven experience in architecting, developing, and maintaining Apache Druid and Imply platforms, with a focus on Dev Ops practices and large-scale system re-architecture
Mastery of building Pipelines in GCP maximising the use of native and native supporting technologies e.g. Apache Airflow
Mastery of Python for data and computational tasks with fluency in data cleansing, validation and composition techniques.
Hands-on implementation and architectural familiarity with all forms of data sourcing i.e streaming data, relational and non-relational databases, and distributed processing technologies (e.g. Spark)
Fluency with all appropriate python libraries typical of data science e.g. pandas, scikit-learn, scipy, numpy, MLlib and/or other machine learning and statistical libraries
Advanced knowledge of cloud based services specifically GCPExcellent working understanding of server-side Linux Professional in managing and updating on tasks ensuring appropriate levels of…