Data Engineer
Actively Reviewing the ApplicationsTOPS Infosolutions Pvt. Ltd.
India, Ahmedabad, Gujarat
Full-Time
INR 12–18 LPA
Posted 3 days ago
•
Apply by June 30, 2026
Job Description
Job Title: Data Engineer
About The Role
We are looking for a highly motivated Data Engineer to join our growing team and play
a critical role in shaping the data foundation of different software platforms. This role sits
at the intersection of data engineering, product, and business stakeholders, and is
responsible for building reliable data pipelines, delivering actionable insights, and
ensuring data quality across systems.
You will work closely with internal teams and external partners to translate business
requirements into scalable data solutions, while maintaining high standards for data
integrity, performance, and usability.
Key Responsibilities
Data Engineering & Architecture
Design, build, and maintain scalable data pipelines and ETL/ELT processes
Develop and optimize data models in PostgreSQL and cloud-native
architectures
Work within AWS ecosystem (e.g., S3, Lambda, RDS, Glue, Redshift, etc.) to
support data workflows
Ensure efficient ingestion and processing of large-scale datasets
Business & Partner Integration
Collaborate directly with business stakeholders and external partners to
gather requirements and deliver reporting solutions
Translate ambiguous business needs into structured data models and
dashboards
Integrate with third-party APIs and other external data sources
Data Quality & Governance
Implement robust data validation, monitoring, and QA processes
Ensure consistency, accuracy, and reliability of data across the platform
Troubleshoot and resolve data discrepancies proactively
Reporting & Analytics Enablement
Build datasets and pipelines that power dashboards and reporting tools
Support internal teams with ad hoc analysis and data requests
Partner with product and engineering teams to embed data into the SaaS product experience
Performance & Scalability
Optimize queries, pipelines, and storage for performance and cost efficiency
Continuously improve system scalability as data volume and complexity grow
Required Qualifications
3–6+ years of experience in Data Engineering or related role
Strong proficiency in Python for data processing and scripting
Advanced experience with PostgreSQL (query optimization, schema design)
Hands-on experience with AWS data architecture (S3, RDS, Lambda, Glue,
Redshift, etc.)
Experience integrating with external APIs
Solid understanding of ETL/ELT pipelines, data modeling, and warehousing
concepts
Experience working cross-functionally with business stakeholders
Preferred Qualifications
Experience in AdTech, eCommerce, or SaaS platforms
Familiarity with BI tools (e.g., Looker, Tableau, Power BI)
Experience with workflow orchestration tools (e.g., Airflow)
Understanding of data governance and compliance best practices
Exposure to real-time or streaming data pipelines
What We’re Looking For
Strong problem-solver who can operate in a fast-paced, ambiguous
environment
Ability to balance technical depth with business context
Excellent communication skills — able to work directly with non-technical
stakeholders
Ownership mindset with a focus on execution and quality
Skills:- Data engineering, Python, AWS Lambda, Amazon Web Services (AWS), ETL and Amazon S3
About The Role
We are looking for a highly motivated Data Engineer to join our growing team and play
a critical role in shaping the data foundation of different software platforms. This role sits
at the intersection of data engineering, product, and business stakeholders, and is
responsible for building reliable data pipelines, delivering actionable insights, and
ensuring data quality across systems.
You will work closely with internal teams and external partners to translate business
requirements into scalable data solutions, while maintaining high standards for data
integrity, performance, and usability.
Key Responsibilities
Data Engineering & Architecture
Design, build, and maintain scalable data pipelines and ETL/ELT processes
Develop and optimize data models in PostgreSQL and cloud-native
architectures
Work within AWS ecosystem (e.g., S3, Lambda, RDS, Glue, Redshift, etc.) to
support data workflows
Ensure efficient ingestion and processing of large-scale datasets
Business & Partner Integration
Collaborate directly with business stakeholders and external partners to
gather requirements and deliver reporting solutions
Translate ambiguous business needs into structured data models and
dashboards
Integrate with third-party APIs and other external data sources
Data Quality & Governance
Implement robust data validation, monitoring, and QA processes
Ensure consistency, accuracy, and reliability of data across the platform
Troubleshoot and resolve data discrepancies proactively
Reporting & Analytics Enablement
Build datasets and pipelines that power dashboards and reporting tools
Support internal teams with ad hoc analysis and data requests
Partner with product and engineering teams to embed data into the SaaS product experience
Performance & Scalability
Optimize queries, pipelines, and storage for performance and cost efficiency
Continuously improve system scalability as data volume and complexity grow
Required Qualifications
3–6+ years of experience in Data Engineering or related role
Strong proficiency in Python for data processing and scripting
Advanced experience with PostgreSQL (query optimization, schema design)
Hands-on experience with AWS data architecture (S3, RDS, Lambda, Glue,
Redshift, etc.)
Experience integrating with external APIs
Solid understanding of ETL/ELT pipelines, data modeling, and warehousing
concepts
Experience working cross-functionally with business stakeholders
Preferred Qualifications
Experience in AdTech, eCommerce, or SaaS platforms
Familiarity with BI tools (e.g., Looker, Tableau, Power BI)
Experience with workflow orchestration tools (e.g., Airflow)
Understanding of data governance and compliance best practices
Exposure to real-time or streaming data pipelines
What We’re Looking For
Strong problem-solver who can operate in a fast-paced, ambiguous
environment
Ability to balance technical depth with business context
Excellent communication skills — able to work directly with non-technical
stakeholders
Ownership mindset with a focus on execution and quality
Skills:- Data engineering, Python, AWS Lambda, Amazon Web Services (AWS), ETL and Amazon S3
Required Skills
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