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Salary
≈ $21k – $42k per year (Estimated)
Location
Remote (India)
Seniority
Senior · 5+ years exp

First seen by Alion on Aug 4, 2026.

Overview
Company
Impact
Profile match
Inumellas Consultancy Services. Accelerated Growth Partners.

Job Overview :

We are seeking an experienced Data Engineer to design, build, and maintain scalable data pipelines and analytical data platforms. In this role, you will be responsible for transforming operational data into reliable, analytics-ready datasets that power reporting, dashboards, and data-driven decision making across our products. You will work closely with backend engineers, frontend engineers, and product teams to ensure high-quality data is available, well-modelled, and easy to consume for analytical use cases.

Responsibilities :

- Design, build, and maintain robust data pipelines to ingest data from transactional systems into analytical data stores.

- Develop efficient ETL/ELT workflows to transform raw data into clean, analytics-ready datasets.

- Model data for analytical workloads, supporting reporting, dashboards, and ad-hoc analysis.

- Manage and optimise analytical data platforms to ensure performance, scalability, and reliability.

- Collaborate with application and frontend engineers to expose data through well-defined interfaces for reporting and dashboarding.

- Ensure data quality, consistency, and integrity through validation, monitoring, and alerting mechanisms.

- Implement data partitioning, indexing, and optimisation strategies to support large scale analytical queries.

- Design and maintain data schemas, documentation, and data contracts for internal consumers.

- Support near real-time and batch data processing use cases as required by the product.

- Work within an agile environment, collaborating with cross-functional teams to deliver data capabilities aligned with business needs.

- Continuously improve data engineering practices, tooling, and architecture.

Required Qualifications / Experience :

- Bachelor's degree in computer science, engineering, mathematics, or a related field, or equivalent practical experience.

- 5+ years of experience as a Data Engineer, building production grade data pipelines and analytical systems.

- Strong experience working with relational databases, particularly PostgreSQL, in transactional environments.

- Hands-on experience with analytical data warehouses such as Amazon Redshift or similar columnar databases.

- Proficiency in SQL, including complex queries, performance tuning, and analytical transformations.

- Experience building ETL/ELT pipelines using modern data engineering tools and frameworks.

- Strong experience with AWS data services and cloud-based data architectures.

- Proficiency in one or more programming languages commonly used in data engineering (e.g., Python).

- Experience with data orchestration and scheduling tools.

- Solid understanding of data modelling concepts for analytics (star schemas, fact/dimension tables).

- Strong understanding of data reliability, quality checks, and monitoring best practices.

Desirable Skills / Experience :

- Experience with streaming or near real-time data pipelines.

- Familiarity with data lake architectures and object storage based analytics.

- Experience supporting BI tools and dashboarding platforms used by product or business teams.

- Understanding of role-based access control and data security in analytical environments.

- Experience with cost optimisation and performance tuning for large-scale analytical workloads.

- Familiarity with CI/CD practices applied to data pipelines.

- Experience working in Agile/Scrum environments and collaborating closely with engineering and product teams.

Work Environment :

This is a fully remote role based in India, with flexible working hours aligned with project needs and team collaboration.

We are looking for someone who can join us as soon as possible and play a key role in building the analytical foundations that support our products and internal insights.

Skills

Data Engineering, AWS, Data Pipeline, ETL, RDBMS, Data Warehousing, Redshift, SQL, Python, Data Modeling

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