Data Scientist at Perfios · Bengaluru (Bangalore) · 4 - 6 years · ₹4L - ₹15L / yr · Posted 26 Sep 2022

1. ROLE AND RESPONSIBILITIES
1.1. Implement next generation intelligent data platform solutions that help build high performance distributed systems.
1.2. Proactively diagnose problems and envisage long term life of the product focusing on reusable, extensible components.
1.3. Ensure agile delivery processes.
1.4. Work collaboratively with stake holders including product and engineering teams.
1.5. Build best-practices in the engineering team.
2. PRIMARY SKILL REQUIRED
2.1. Having a 2-6 years of core software product development experience.
2.2. Experience of working with data-intensive projects, with a variety of technology stacks including different programming languages (Java,
Python, Scala)
2.3. Experience in building infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data
sources to support other teams to run pipelines/jobs/reports etc.
2.4. Experience in Open-source stack
2.5. Experiences of working with RDBMS databases, NoSQL Databases
2.6. Knowledge of enterprise data lakes, data analytics, reporting, in-memory data handling, etc.
2.7. Have core computer science academic background
2.8. Aspire to continue to pursue career in technical stream
3. Optional Skill Required:
3.1. Understanding of Big Data technologies and Machine learning/Deep learning
3.2. Understanding of diverse set of databases like MongoDB, Cassandra, Redshift, Postgres, etc.
3.3. Understanding of Cloud Platform: AWS, Azure, GCP, etc.
3.4. Experience in BFSI domain is a plus.
4. PREFERRED SKILLS
4.1. A Startup mentality: comfort with ambiguity, a willingness to test, learn and improve rapidl

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3 5+ years of experience in developing highly scalable REST/Web APIs
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6 Strong understanding of object-oriented programming and possess strong fundamental design principles for building a scalable application.
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8 Strong understanding of object-oriented programming and possess strong fundamental design principles for building a scalable application.
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12 Development experience with data integration technologies including REST, SOAP, JSON, XML
13 Expertise in programming and usage of any unit testing framework. Expertise in integration testing and continuous integration.
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Data Engineer – Microsoft Fabric
Location: Pune, India
Work Mode: Hybrid
Experience: 6+ Years
Employment Type: Full-time contactor
Compensation: As per market standards, commensurate with experience and expertise
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About the Role
Jade Business Services (JBS) is seeking a Data Engineer – Microsoft Fabric to join our Pune team and work on enterprise-scale data transformation and analytics initiatives.
We are looking for a hands-on Data Engineer with strong experience in Microsoft Fabric, SQL, Python/PySpark and modern data engineering practices. The candidate will be responsible for building scalable data pipelines, implementing Lakehouse and Warehouse solutions, developing data models and supporting governed, reliable and AI-ready data platforms.
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- Design and develop data solutions using Microsoft Fabric, including OneLake, Lakehouse, Warehouse and Data Factory pipelines.
- Build and maintain scalable ETL/ELT pipelines for batch and incremental data processing.
- Develop data ingestion and transformation pipelines using Fabric Data Factory, SQL, Python and/or PySpark.
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- Implement data quality, validation, monitoring and error-handling mechanisms.
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- Support Data Product and domain-oriented data architecture principles.
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- Troubleshoot pipeline failures, performance issues and data quality problems.
- Optimize data pipelines, queries and storage for performance and cost efficiency.
- Work closely with Data Architects and business stakeholders to understand requirements and implement technical solutions.
- Participate in technical design discussions, code reviews and architecture reviews.
- Maintain technical documentation, data flow diagrams and pipeline documentation.
- Support production deployments, incident resolution and SLA-driven data platform operations.
- Identify opportunities for automation and AI-assisted improvements across data engineering processes.
Qualifications and Skills
- 6+ years of experience in Data Engineering, Data Integration or Data Platform development.
- Strong hands-on experience with Microsoft Fabric.
- Experience with:
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- OneLake
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- Semantic Models
- Strong understanding of Lakehouse and Medallion Architecture.
- Strong SQL development and query optimization skills.
- Hands-on experience with Python and/or PySpark.
- Experience developing enterprise ETL/ELT and data integration pipelines.
- Experience with batch and incremental data processing.
- Understanding of data modelling concepts including dimensional modelling.
- Knowledge of data quality, metadata, lineage and data governance.
- Working knowledge of Microsoft Purview.
- Understanding of Data Mesh and Data Product concepts.
- Experience with CI/CD, version control, monitoring and DataOps practices.
- Understanding of cloud security, access controls and data privacy.
- Good troubleshooting and problem-solving skills.
- Strong communication skills and ability to work with distributed and client-facing teams.
Preferred Skills
- Microsoft Fabric or Azure Data certifications.
- Experience migrating workloads from Azure Synapse, SQL Server, Databricks or other data platforms to Microsoft Fabric.
- Experience implementing Medallion Architecture on Microsoft Fabric.
- Experience with Power BI and semantic modelling.
- Exposure to AI/ML, Generative AI or Agentic AI use cases on enterprise data platforms.
- Experience working with Data Products or domain-oriented data solutions.
- Experience in Energy & Utilities, Healthcare, Financial Services or Insurance.
- Experience working with US or international enterprise clients.
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The ideal candidate should be hands-on first and capable of independently building, troubleshooting and optimizing Fabric data solutions. You should be able to explain the technical decisions behind your implementation and work effectively with architects and engineering teams to deliver production-ready solutions.
4 - 10 years of experience in designing and buildingarchitecting highly resilient data platforms
∙Strong knowledge of data engineering, architecture and data modeling
∙Experience in platforms like Databricks and Snowflake
∙Experience on building applications on cloud (AWS or Azure or Google Cloud)
∙Strong analytical and problem-solving skills
∙Prior experience in developing data or computation intensive (e.g. grid based) backend applications is an
advantage
∙OOP design skills with an understanding or at least personal interest towards the concepts of Functional
Programming
∙Willingness to understand and enhance other people’s code, being able to work in an environment where
developers will oversee and work on wider components also dealing with older “legacy” code
∙Strong programming skills (Java/ Scala / Python) skills with the willingness to pick up the other language if not
already mastered at a sufficient level is important
∙Spring knowledge is an advantage, but in general willingness to learn, work with and even enhance in-house
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∙Prior experience in working with Git, Bitbucket, Jenkins, working with PR-s, using JIRA, following the Scrum Agile
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∙Prior knowledge of financial products is an advantage
∙Bachelors or Masters in any relevant field of IT/Engineering area is an advantage
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.
Headquartered in the United States with a Global Delivery Center (GDC) in Noida, India, 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 Senior Data Engineer with strong data engineering and database expertise to design, build, optimize, and support enterprise-scale data solutions.
This is a hands-on engineering position requiring strong SQL, Python, ETL/ELT, database, cloud, and troubleshooting capabilities. The engineer will work closely with technical leads and client stakeholders while taking ownership of major engineering components.
Location: Noida, India – Onsite | Employment Type: Full-Time | Experience: 6–9 Years
Key Responsibilities
Data Engineering
- Design, develop, test, deploy, and support scalable ETL/ELT pipelines.
- Build ingestion and transformation solutions across databases, APIs, files, and enterprise applications.
- Develop high-quality SQL and Python-based data processing solutions.
- Implement batch and incremental data-processing patterns.
- Develop reusable engineering components and frameworks.
- Support complex data migration and transformation activities.
- Perform source-to-target mapping and technical data analysis.
- Implement pipeline logging, monitoring, exception handling, and recovery mechanisms.
Database & Platform Engineering
- Design and optimize relational database schemas and data structures.
- Analyze and improve SQL/query performance.
- Support indexing, partitioning, storage optimization, and database performance.
- Implement appropriate database security and access controls.
- Support database monitoring, availability, backup/recovery, and operational requirements in collaboration with infrastructure/platform teams.
- Troubleshoot database and pipeline performance issues.
- Contribute to cloud data-platform configuration and optimization.
Data Quality
- Implement automated validation and data-quality controls.
- Develop reconciliation processes between source and target systems.
- Identify duplicate, incomplete, inconsistent, and invalid data.
- Implement cleansing, standardization, validation, and exception-management logic.
- Work with technical and business stakeholders to understand and implement business data rules.
Technical Delivery
- Convert technical designs into reliable production solutions.
- Participate in technical design and code reviews.
- Mentor junior/mid-level engineers.
- Support estimation and technical planning.
- Troubleshoot complex production and integration issues.
- Collaborate with technical leads, application teams, DevOps, QA, BI, and client teams.
- Document technical designs, mappings, configurations, operational procedures, and engineering decisions.
Consulting & AI-Led Working
- Understand the business purpose behind assigned engineering requirements.
- Raise risks, assumptions, dependencies, and potential improvements proactively.
- Communicate effectively with client and internal stakeholders.
- Use AI-assisted tools to improve coding, testing, analysis, documentation, and troubleshooting productivity.
- Independently verify AI-generated code and recommendations before implementation.
- Identify opportunities for engineering automation and process improvement.
Required Qualifications
- 6–9 years of experience in data engineering, database engineering, data integration, or related areas.
- Advanced SQL skills.
- Strong hands-on Python experience.
- Strong ETL/ELT development experience.
- Strong relational database knowledge, such as SQL Server, PostgreSQL, Oracle, or equivalent.
- Experience with data modeling and database design.
- Experience with AWS, Azure, or another major cloud platform.
- Experience with modern data technologies such as Databricks, Snowflake, Redshift, Synapse, Glue, ADF, Airflow, dbt, or equivalent.
- Experience with performance tuning and optimization.
- Experience with data validation and reconciliation.
- Strong troubleshooting and analytical skills.
- Ability to take ownership of engineering deliverables with limited supervision.
Preferred Qualifications
- Experience working with enterprise ERP, CRM, PIM, PLM, MES, or related systems.
- Experience with manufacturing, retail, distribution, or consumer-goods data.
- Experience with CI/CD and infrastructure/platform engineering practices.
- Experience with API and event-driven integrations.
- Previous consulting or technology-services experience.
What Success Looks Like
- Pipelines and databases perform reliably at enterprise scale.
- Engineering solutions are maintainable, reusable, and well documented.
- Data issues are detected and addressed systematically.
- Junior engineers receive effective technical guidance.
- Problems are owned through resolution rather than simply escalated.
- Engineering decisions reflect both technical requirements and client business objectives.
Job Summary
We are looking for a skilled and experienced Data Engineer to join our growing data team. The ideal candidate will have strong expertise in Python, PySpark, Data Modeling, and Power BI, with hands-on experience in designing, developing, and optimizing scalable data solutions. The role requires working closely with business stakeholders, data architects, and analytics teams to build robust data pipelines and semantic models that enable data-driven decision-making.
Technical Skills
- Strong hands-on experience in Python and PySpark development.
- Expertise in building and optimizing Data Engineering solutions and ETL pipelines.
- Strong understanding of Data Modeling concepts (Star Schema, Snowflake Schema, Dimensional Modeling).
- Experience with Power BI Data Modeling and Semantic Layer development.
- Proficiency in DAX (Data Analysis Expressions).
- Experience designing and managing Semantic Models in Power BI.
- Strong SQL skills and experience working with large datasets.
- Knowledge of data warehousing concepts and best practices.
Preferred Skills
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Exposure to modern data platforms like Databricks.
- Understanding of data governance and data quality frameworks.













