Data Engineering & Analytics Manager

Nat Habit; Gurugram District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Nat Habit is hiring a Data Engineer + Analyst to build production‑grade data systems and drive business analytics. You will lead a team designing reliable data pipelines and develop insights that inform strategy.

This role suits engineers who relish solving real data engineering problems, writing clean code, and scaling data platforms to empower business decisions.

Qualifications

• Strong Python experience with data engineering and analytics.
• Experience building scalable ETL/ELT pipelines.
• Proficient in SQL and OLAP databases (ClickHouse, Redshift).
• Hands-on with BI tools like Tableau/Metabase.

Responsibilities

• Lead analysts and engineers to deliver insights and monthly reports.
• Design, build and maintain data pipelines and ingestion workflows.
• Develop dashboards and consumer insights using BI tools.
• Define analytical data models and reporting datasets.
• Optimize query performance and data storage efficiency.
• Enforce data governance, security, and lifecycle policies.

Skills

Python programming

Pandas

NumPy

PySpark

SQL

ETL/ELT

Airflow

Dagster

dbt

ClickHouse

Redshift

Docker

Git

Tableau

Metabase

Data governance

Tools

Dagster

Airflow

dbt

ClickHouse

Redshift

Docker

Metabase

Tableau

Job description

At Nat Habit, we are building efficacious personal care using natural ingredients while doing primary research to build formulations from a first principle basis to find cures, study the underlying impact on different markers and then conduct clinical studies to prove efficacy of products. Check us out on www.nathabit.in

The founding team has a strong startup experience and is well funded and backed by top angel investors and tier 1 institutional investors.

Job Summary:

Nat Habit is looking for a Data Engineer + Analyst who enjoys building production-grade data systems as well as data analysis. You will lead a team responsible for designing & developing reliable data pipelines and drive business analytics and intelligence in the organization.

This role is ideal for engineers who enjoy solving real engineering problems, writing clean code, building scalable data platforms and driving business insights

Key Responsibilities:

• Lead a team of analysts and engineers to create insights and monthly reporting within organization
• Design, build and maintain scalable ETL/ELT pipelines using SQL, Python and tools such as Dagster, Airflow or dbt to ingest, transform and load data into data platforms.
• Develop scalable and reliable data ingestion workflows.
• Create BI reports and leverage AI to build dashboard and consumer insights
• Design reporting datasets and analytical data models.
• Work extensively with ClickHouse or other OLAP database for analytical workloads.
• Optimize query performance, data storage and processing efficiency through advanced SQL techniques, partitioning, indexing strategies and workload optimization.
• Define and enforce data governance policies including data security, access control, masking and lifecycle management within data platforms.

Ideal candidate will have:

• Strong proficiency in Python, including Pandas, NumPy, PySpark.
• Hands on experience with ETL / ELT and data integration tools, such as Apache Airflow, Pentaho, or Dagster
• One or more years of experience with RDBMS and OLAP databases like Clickhouse, Redshift.
• Good working knowledge of containers like Docker or Podman
• Experience building analytics report using Tableau, Metabase or other BI tools
• Should have good understanding & knowledge about observability.
• Experience in version control tool: Git

Do not apply if following is applicable to you:

• Backend engineers who only enjoy request/response APIs and CRUD, and don’t want to own end-to-end data pipelines, scheduling, and reliability.
• Engineers who do not have experience with business intelligence and related tooling.
• Data analysts who mainly write ad-hoc SQL and build dashboards, and do not have engineering experience eg: version control, testing, CI/CD, and data infrastructure.
• People who don’t naturally question data quality – if obviously wrong or inconsistent metrics don’t bother you, this won’t be a good fit.

Work

www.nathabit.in

www.instagram.com/nathabit.in

Working Days: Mon - Sat (2nd/4th Sat are off)