Data Engineer – Integration & Data Quality

Company: Solutionara Private Limited

Location: Noida, India – Onsite

Employment Type: Full-Time

Experience: 3–6 Years

About Solutionara

Solutionara is an AI-led IT Consulting and Technology Services organization delivering enterprise transformation through Cloud, Integration, Data Engineering, Digital Experience, AI, and Enterprise Applications.

Solutionara partners with enterprise organizations across retail, manufacturing, distribution, consumer goods, and other industries to design, implement, and support scalable technology solutions.

As a rapidly growing consulting organization, we foster a culture of ownership, innovation, collaboration, and continuous improvement, empowering our teams to contribute beyond their immediate responsibilities while delivering exceptional value to our global clients.

Every team member is expected to think like a consultant and business problem solver— understanding client objectives, challenging assumptions when appropriate, leveraging AI responsibly, and continuously identifying opportunities to improve quality, productivity, and customer outcomes.

AI is embedded into how we work, but it is an enabler—not a replacement for expertise, critical thinking, or accountability.

Role Overview

Solutionara is seeking a hands-on Data Engineer – Integration & Data Quality to develop enterprise data pipelines while ensuring that data moving between systems is accurate, complete, consistent, and reliable.

This role combines traditional data engineering with data-quality engineering and is ideal for someone who enjoys investigating data problems as much as building pipelines.

Key Responsibilities

Data Engineering & Integration

- Develop, test, and maintain ETL/ELT pipelines.
- Ingest data from databases, APIs, flat files, cloud storage, and enterprise applications.
- Develop data transformations using SQL, Python, and relevant data-engineering technologies.




- Implement source-to-target mappings.
- Support batch and incremental data-processing patterns.
- Build reusable components for ingestion, transformation, and validation.
- Support data migration and integration activities.
- Monitor pipelines and troubleshoot processing failures.

Data Quality
- Perform data profiling and identify anomalies, inconsistencies, duplicates, and missing data.
- Develop automated data-quality rules and validation processes.
- Implement cleansing and standardization logic.
- Perform source-to-target reconciliation.
- Validate referential integrity and relationships across datasets.
- Develop duplicate-detection and exception-handling processes.
- Maintain data-quality logs, reports, and issue records.
- Perform root-cause analysis for recurring data-quality problems.
- Work with business and technical stakeholders to translate business rules into executable validations.

Engineering & Delivery
- Write clean, maintainable, and testable code.
- Participate in peer code reviews.
- Develop unit and data-validation tests.
- Follow established engineering, security, and documentation standards.
- Collaborate with senior engineers, application teams, QA, BI, and client stakeholders.
- Document mappings, transformation rules, validation rules, and technical configurations.
- Proactively raise data anomalies, technical risks, and dependencies.

Consulting & AI-Led Working
- Understand why data is being processed and how it supports the client's business processes.
- Ask questions when requirements or data behavior appear inconsistent.




- Use AI-assisted tools responsibly for development, analysis, testing, documentation, and troubleshooting.
- Validate AI-generated outputs rather than treating them as authoritative.
- Identify opportunities to automate repetitive data-quality and engineering activities.

Required Qualifications

- 3–6 years of experience in data engineering, ETL development, data integration, or related areas.
- Robust SQL skills.
- Working proficiency in Python.
- Experience developing ETL/ELT pipelines.
- Experience working with relational databases.
- Experience integrating data through APIs, databases, files, or cloud storage.
- Understanding of data modeling and source-to-target mapping.
- Experience with data validation, profiling, cleansing, or reconciliation.
- Familiarity with AWS, Azure, or modern cloud data platforms.
- Strong analytical and troubleshooting skills.

Preferred Qualifications

- Experience with Databricks, Snowflake, Redshift, Synapse, Glue, ADF, Airflow, dbt, or similar technologies.
- Experience with enterprise application data, including ERP, CRM, PIM, PLM, or related platforms.
- Experience working with product, customer, supplier/vendor, material, location, or reference data.
- Exposure to manufacturing, retail, distribution, or consumer-goods environments.
- Experience in consulting or client-facing technology delivery.

What Success Looks Like

- Data pipelines operate reliably and produce trusted outputs.
- Data-quality problems are detected early rather than discovered downstream.
- Validation and reconciliation are automated wherever practical.
- Data issues are investigated to root cause.
- Engineering deliverables meet technical standards and business requirements.
- You progressively take ownership of larger and more complex engineering components.

Pay: ₹1,000,000.00 - ₹1,500,000.00 per year

Work Location: In person

📌 Data Engineer- Integration & Data Quality (Noida)
🏢 Solutionara
📍 Noida