Job Description

As a Data Engineer, you'll play a crucial role in managing the entire lifecycle of data pipelines and integrating data visualization solutions.

Data Pipeline Creation:

Collaborate with Product Owners and business representatives to define new data pipelines technically.

Evaluate the complexity associated with each ambition and the required skills.

Work closely with subject matter experts to determine the necessary scope of data for fueling the pipelines.

Design and co-build the architecture for ingesting data, considering data cleansing and preparation based on its origin.

Implement the data transformation layer, leveraging analytics or AI features.

Establish connections with external services to expose output data.

Data Visualization:

Utilize Power BI capabilities to share various datasets with internal teams and external customers.

Develop dashboards for automating the monitoring of AI features and adoption.

Create customer reports that showcase data transformation results, following guidance from our business representatives and Connected Services Hubs remote support agents.

Actively contribute to integrating Power BI into the program for creating a new reporting experience.

Collaborate with UX designers to structure reporting concepts (events, evidence, recommendations).

Identify all detailed data models.

Build a semantic database to anticipate future needs, including Generative AI Co-Pilot integration.

Deploy and maintain report templates.

DevOps / MLOps role:

Masters model deployment and upgrade in the appropriate environment (Databricks, Dataiku, others...)

Knowledgeable around the correct implementation of those environment in Azure (or similar environment like AWS or GCP)

Act as a single point of contact for the analytics team with external technical DevOps organization (Advisor Engineering, AI Hub)

Qualifications

Experience 10-12+ years

Python Programming (5/5): Strong programming skills are essential for data manipulation, transformation, and pipeline development.

ETL Extract Transfer Load (5/5): Significative experience is required

Data Preparation and Modeling (5/5): Understanding various kind of data structures will be valuable in the role.

Sql / Non Sql DB Management (4.5/5): Proficiency in Database Management systems

MLOps (4/5): Understanding ML concepts for integrating ML models into pipelines.

DevOps (Azure) (4/5): Familiarity with Azure cloud services for scalable data storage and processing.

Databricks (3/5): Proficiency with Databricks environment will be valuable

Dataiku (1.5/5) : an experience with Dataiku platform could be a plus


Power BI usage (5/5): Ability to create insightful visualizations in Power BI is mandatory

Primary Location

:

IN-Karnataka-Bangalore

Schedule

:

Full-time

Unposting Date

:

Ongoing