Senior Data Engineer

Location: Bangalore
Experience: 4+ years in data analysis, engineering, or data management
Compensation: Competitive

Noora Health

Noora Health's mission is to improve health outcomes by training family members to care for their loved ones. Founded in 2014, they turn hospital hallways into classrooms. Working with governments in India, Bangladesh, Indonesia, and Nepal, Noora Health has trained over 35 million caregivers in more than 12,600 health facilities. Their Care Companion Program (CCP) has been shown to significantly reduce post-surgical complications for cardiac patients by 71% and newborn mortality by 18%. Noora Health is an Audacious Project Grantee and a recipient of the Skoll Foundation Award for Social Innovation.

Role

You will be responsible for expanding and maintaining our central data system. This involves integrating new data sources, building strong data pipelines, and helping design data policies across all the geographies we operate in.

Responsibilities

Design, develop, and maintain scalable data pipelines, ETL processes, and data warehouse structures to ensure data quality and accessibility.
Collaborate with various teams to gather requirements, develop data models, and design analytics solutions that address specific needs.
Implement data governance and security measures for the regions we operate in.
Support data analysts and monitoring teams to build dashboards and communicate insights back to the larger team.
Manage our data warehouse and ensure databases perform well for querying and dashboarding.
Develop and maintain data visualisations and dashboards to track key performance indicators (KPIs).
Support the engineering team in refining schemas for our applications based on stakeholder requirements.

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
4+ years of proven experience in data analysis, engineering, data management or other equivalent fields.
Knowledge of data warehousing, database design, and data modelling techniques.
Strong proficiency in SQL, Python, and data manipulation languages (DML).
Hands-on experience with data pipeline and ELT/ETL tools (e.g., Fivetran, Airbyte, dbt).
Familiarity with cloud-based data warehouse and data processing platforms (e.g., BigQuery, Snowflake, Databricks).
Proficiency in data visualisation and reporting tools (e.g., Tableau, Metabase, Superset, PowerBI).
Strong analytical, problem-solving, and communication skills, with the ability to explain complex data to non-technical people.
Detail-oriented, self-motivated, and able to work independently as well as in a team.