Data Engineer I
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 11h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 10d ago
The date the source published, not the day we noticed it (2026-09-21). Last seen at its source 1h ago.
We have tracked this listing since 21 Sep 2026 (10 days). The employer's own board has carried it every time we have read it, most recently 1 hour ago.
Is it remote?
Remote - India
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
India
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $6,438–7,250/mo
Middle 50% of 8 listings that do state pay — Engineering · all levels · India · USD/month. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
lever employer's own board first seen 10d ago · last seen 1h ago
The listing
Netomi is seeking a highly analytical and detail-oriented candidate to join the Analytics team in Gurugram. As part of the team, you will work with data science, product, engineering, and customer success teams to drive complex data and trend analyses to propose ways to improve and thereby contribute to improving the experience. You will also be responsible for benchmarking and measuring the performance of various product operations projects, building and publishing detailed scorecards and reports, identifying and driving new opportunities based on customer and business data.
We are looking for an Engineer with a passion for using data to discover and solve real-world problems. You will enjoy working with rich data sets, modern business intelligence technology, and the ability to see your insights drive the features for our customers. You will also have the opportunity to contribute to the development of policies, processes, and tools to address product quality challenges in collaboration with teams.
Responsibilities
- Architect and implement scalable, secure, and reliable data pipelines using modern data platforms (e.g., Spark, Databricks, Airflow, Snowflake, etc.).
- Develop ETL/ELT processes to ingest data from various structured and unstructured sources.
- Perform Exploratory Data Analysis (EDA) to uncover trends, validate data integrity, and derive insights that inform data product development and business decisions.
- Collaborate closely with data scientists, analysts, and software engineers to design data models that support high-quality analytics and real-time insights.
- Write clean, maintainable code with comprehensive unit and integration tests to ensure reliability and stability in Python.
- Thrive in an agile, collaborative environment and take ownership of end-to-end feature delivery.
Requirements:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 2+ years of hands-on experience in data engineering or backend software development roles.
- Solid understanding of Relational Databases (RDS, MySQL, PostgreSQL).
- Experience with Apache Kafka or RabbitMQ for building asynchronous, decoupled systems.
- Proficiency with Python, SQL, and at least one data pipeline orchestration tool (e.g., Apache Airflow, Luigi, Prefect).
- Strong experience with cloud-based data platforms (e.g., AWS Redshift, GCP BigQuery, Snowflake, Databricks).
- Deep understanding of data modeling, data warehousing, and distributed systems.
Additional Skills
- Familiarity with DevOps practices (CI/CD, infrastructure as code, containerization with Docker/Kubernetes).
- Exposure to AI/ML-integrated solutions or interest in working alongside data science teams.
- Knowledge of data security and privacy regulations (e.g., GDPR, HIPAA).
- Familiarity with prompt engineering and how LLM-based systems interact with data.