Test Data Engineer,

Role Overview

We are seeking a skilled Senior Data Analyst with substantial hands-on experience in Source System Analysis, data mapping, data modeling, SQL analysis, and integration testing. The ideal candidate will support seamless data flow across business applications, ensure data accuracy, and contribute to system improvements.

Key Responsibilities

• Conduct detailed data mapping between source and target systems, ensuring consistency and accuracy.
• Build and maintain data models to support business processes, reporting needs, and integration workflows.
• Write and optimize SQL queries for data validation, analysis, migration, and troubleshooting.
• Work closely with cross-functional teams to gather data requirements and understand business logic.
• Develop and execute integration test plans, including functional, data validation, and regression testing.
• Support data migration activities, including extraction, transformation, and loading (ETL).
• Monitor and troubleshoot integration issues, ensuring timely resolution.
• Document integration flows, data dictionaries, mapping catalogs, and knowledge artifacts.
• Ensure integration security, data integrity, and compliance with organizational standards.

Required Skills & Qualifications

• 5+ years of experience insource system integrations, data mapping, and system-to-system data workflows.
• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
• Hands-on experience with data mapping, data modelling, and database schema design.
• Proficiency in SQL (complex joins, stored procedures, performance tuning).
• Experience with ETL tools or integration platforms (Informatica, Boomi, MuleSoft, Talend, Pentaho).
• Strong analytical and problem-solving skills.
• Experience with API-based integrations (REST/SOAP) is a plus.
• Familiarity with testing methodologies for integrations and data validation.
• Ability to work with business users, understand workflows, and translate requirements into technical solutions.

Preferred Qualifications

• Experience with cloud ERP or cloud integration (AWS/Azure/GCP).
• Knowledge of JSON, XML, CSV transformation.
• Exposure to scripting languages (Python, Shell).
• Experience in Agile/Scrum environments.
• Prior involvement in ERP implementation or upgrade projects.

Competencies

• Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.
• Self-Development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.
• Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
• Customer Focus - Building strong customer relationships and delivering customer-centric solutions.
• Optimize Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.

Why Join Us?

• Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
• Work on impactful projects that make a difference across industries.
• Opportunities for professional growth and continuous learning.
• Competitive salary and benefits package.

Application Details

Ready to make an impact? Apply today and become part of the QX Impact team!

We are looking for Data engineer with strong expertise in Data warehousing to join our team.

Key skills : ab initio, ssis , Informatica, Hadoop and Teradata

Job Description

We are looking for an experienced Data Engineer with strong expertise in Python, ETL, SQL, CI/CD, and DevOps to design, develop, and maintain scalable data pipelines and data processing solutions.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines.
• Develop data processing solutions using Python.
• Write complex and optimized SQL queries, stored procedures, and data transformations.
• Build and maintain data ingestion and integration workflows.
• Implement data quality, validation, monitoring, and error-handling processes.
• Develop and maintain CI/CD pipelines for data engineering applications.
• Work with DevOps tools and practices for automated build, deployment, and infrastructure management.
• Collaborate with data analysts, data scientists, software engineers, and business teams.
• Optimize data pipelines for performance, reliability, and scalability.
• Troubleshoot production data issues and ensure timely resolution.
• Follow best practices for version control, code quality, testing, and deployment.

Mandatory Skills

• Python
• ETL
• SQL
• CI/CD
• DevOps
• Git / Version Control
• Strong problem-solving and debugging skills

Job Summary

Role Overview

We are looking for an experienced Data Engineer with strong expertise in Python, ETL, Advanced SQL, CI/CD, DevOps, and Data Analytics. The ideal candidate should have hands-on experience designing and developing scalable data pipelines, transforming large datasets, and supporting data-driven applications.

Experience with Google Cloud Platform (GCP) will be an added advantage.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL.
• Develop complex and optimized SQL queries, stored procedures, and data transformations.
• Build and maintain reliable data integration workflows across multiple data sources.
• Perform data cleansing, validation, transformation, and quality checks.
• Analyze data and provide insights to support business and technical requirements.
• Implement and maintain CI/CD pipelines for data engineering applications.
• Work with DevOps practices and tools to automate deployments, monitoring, and infrastructure processes.
• Troubleshoot data pipeline failures, performance issues, and production incidents.
• Optimize data processing workflows for performance, scalability, and reliability.
• Collaborate with Data Analysts, Data Scientists, Developers, and other stakeholders.
• Follow best practices for version control, testing, documentation, and deployment.
• Contribute to cloud-based data engineering initiatives, preferably on GCP.

Required Skills

• 5–7 years of hands-on experience in Data Engineering.
• Strong programming skills in Python.
• Strong expertise in Advanced SQL and database concepts.
• Hands-on experience with ETL/ELT processes and data pipelines.
• Good understanding of Data Warehousing and Data Modeling concepts.
• Experience with CI/CD practices and tools.
• Strong understanding of DevOps principles, automation, and deployment processes.
• Strong data analytics and problem-solving skills.
• Experience working with large datasets and performance optimization.
• Good understanding of Git/version control and software development best practices.

Good to Have

• Hands-on experience with Google Cloud Platform (GCP).
• Exposure to GCP data services such as BigQuery, Cloud Storage, Dataflow, Composer, or Pub/Sub.
• Experience with containerization/orchestration technologies such as Docker/Kubernetes.
• Experience with workflow orchestration tools such as Airflow.
• Knowledge of cloud-based data architecture and distributed data processing.

Preferred Candidate Profile

• Strong analytical and problem-solving abilities.
• Good communication and stakeholder management skills.
• Ability to work independently as well as in a collaborative team environment.
• Strong ownership of data pipelines and production systems.
• Candidates who can join at short notice are preferred.

Mandatory Skills

 Data Engineer, Python , ETL, GCP, Advanced SQL, Strong Data Analytics skills, CICD, Devops

Location: Hyderabad / Chennai

Experience: 5+ years

Employment type: Full-time, permanent

Work Hours: General Shift

website: www.amazech.com

Qualifications: 

• B.E./B.Tech/M.E./M.Tech in Computer Science, Information Technology, Data Science, or related disciplines.
• Strong academic background with relevant industry experience in Data Engineering and Data Warehousing.

Key Responsibilities:

·       Design, develop, and maintain scalable data warehouse solutions using Snowflake.

·       Write, optimize, troubleshoot, and enhance Snowflake SQL queries with a focus on performance and scalability.

·       Develop and support ETL processes using Talend to ensure reliable and efficient data movement.

·       Collaborate with business, analytics, and application teams to enable reporting, dashboards, metrics, and data exploration capabilities.

·       Perform data analysis and resolve issues across data ingestion, transformation, and reporting pipelines.

·       Debug and troubleshoot Python-based data processing scripts and automation workflows.

·       Implement best practices for data quality, testing, deployment, and code reviews.

·       Work across UI, API, and Data Warehouse layers to support end-to-end data integration and business requirements.

·       Monitor, optimize, and maintain data warehouse performance and operational stability.

·       Create and maintain technical documentation, data models, and process workflows.

Required Skills and Experience: 

·       Strong hands-on expertise in Snowflake Data Warehouse.

·       Advanced SQL skills with experience handling large-scale datasets.

·       Strong understanding of Data Warehousing concepts, dimensional modelling, and data architecture.

·       Hands-on experience with Analytical SQL functions, query tuning, and performance optimization.

·       Experience developing and maintaining ETL solutions using Talend.

·       Proficiency in Python for scripting, debugging, automation, and data processing.

·       Experience integrating UI, API, and Data Warehouse workflows.

·       Strong problem-solving and analytical skills.

·       Experience with testing, code reviews, and deployment best practices.

·       Excellent communication and stakeholder management skills.

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.

Senior Quality Engineer

Notice Period: Immediate

Purpose of the Job:

We are seeking a highly skilled and experienced Senior Quality Engineer to join our Enterprise Technology and Data team. This role is crucial in ensuring the delivery of high-quality data-driven solutions and applications across our enterprise systems. The ideal candidate will have deep expertise in quality engineering, automated testing, and extensive experience in testing large-scale data systems, particularly in ETL processes and working with Azure Fabric and Google Cloud data platforms such as BigQuery and Google Cloud Data Pipelines.

As a Senior Quality Engineer, you will be responsible for defining and implementing quality assurance processes, developing automated tests, identifying and mitigating risks, and ensuring the overall quality of our technology and data platforms across multi-cloud environments (Azure and Google Cloud Platform). You will work closely with cross-functional teams including developers, data engineers, and product managers to ensure that the highest standards of quality are maintained throughout the software development lifecycle.

Main Activities:

1. · Test Planning & Execution: Design detailed test strategies/plans, test cases, and test scripts to validate data accuracy, integrity, and system functionality in ETL pipelines across Azure and GCP (e.g., Dataflow, Data Fusion, BigQuery pipelines), including both functional and non-functional testing.
2. · Data Quality: Collaborate with data engineers to monitor and ensure the accuracy, completeness, and consistency of data across various data platforms including Azure Synapse/Fabric and Google BigQuery, validating transformations and data integrity in ETL pipelines.
3. · Data Pipeline Testing: Collaborate with data engineering teams to design and execute tests for Data pipelines running on Azure Fabric as well as Google Cloud services such as Dataflow, Dataproc, and Pub/Sub-based pipelines, ensuring transformation, integration, and storage processes function as expected.
4. · SQL Database Testing: SQL Database Testing: Development and execution of SQL-based automated tests for database validation, ensuring data integrity, performance, and security across multiple databases including BigQuery datasets and Azure SQL/Synapse environments.
5. · Performance Testing: Conduct performance testing to evaluate the scalability, stability, and performance of large-scale data systems across distributed cloud platforms including Azure and GCP.
6. · Automated Testing: Develop and maintain automated test frameworks for data applications, including ETL processes, APIs, and data integration systems using industry-standard tools, and extend automation to support BigQuery validation, GCP pipeline testing, and AI/ML data validation scenarios.
7. · Defect Tracking & Resolution: Work with development and operations teams to identify, report, and track defects across multi-cloud data ecosystems, ensuring timely resolution.
8. · Continuous Improvement: Propose and implement improvements to testing processes and frameworks to increase efficiency and effectiveness of quality assurance efforts across Azure and Google Cloud-based data platforms and AI-enabled data solutions.
9. · Collaboration: Partner with business stakeholders, project managers, and technical teams to ensure alignment with quality goals and deliverables across enterprise data platforms spanning multiple cloud providers.
10. · Mentorship: Provide guidance and mentorship to junior quality engineers, helping them improve their technical skills in modern data testing practices including cloud-native and AI-driven validation techniques.
11. · Compliance & Best Practices: Ensure adherence to industry standards and best practices related to software quality, particularly in relation to data systems, ETL processes, and cloud technologies including Azure and Google Cloud Platform environments.

Knowledge/Skill Requirements:

· Education:

1. o Bachelor’s degree in computer science, Information Technology, Engineering, or a related field.
2. · Experience:
3. o 5+ years of experience in software quality engineering, with at least 3 years of experience in an enterprise data environment.
4. o Proven experience in automated testing tools (e.g., Selenium, JUnit, TestNG, or similar frameworks).
5. o Hands-on experience with data validation, transformation, and data pipeline testing in cloud environments, specifically Azure and/or Google Cloud Platform (GCP).
6. o Strong understanding of data management, data warehousing, ETL processes, and data integration.
7. o Experience with data warehousing, data lakes, and cloud-based ETL tools including Azure Data Factory, Azure Synapse, Google BigQuery, Dataflow, and Dataproc is a plus.

Technical Skills:

1. o Proficient in scripting languages (e.g., Python, Java, SQL) for test automation and ETL process validation.
2. o Experience working with Azure Data Factory, Azure Synapse Analytics, Microsoft Fabric, as well as Google Cloud services such as BigQuery, Dataflow and Cloud Composer (Airflow) for data pipeline orchestration and validation.
3. o Strong knowledge of software development methodologies (Agile, Scrum, Waterfall) and experience in a continuous integration/continuous deployment (CI/CD) environment.
4. o Familiarity with version control systems (e.g., Git), CI/CD tools (e.g., Jenkins, Azure DevOps), and cloud infrastructure (e.g., Azure, GCP).
5. · Soft Skills:
6. o Strong analytical, problem-solving, and troubleshooting skills.
7. o Excellent communication skills, with the ability to collaborate effectively across departments.
8. o Detail-oriented with a passion for ensuring high-quality standards in data-driven solutions.
9. o Ability to work independently and as part of a team, managing multiple priorities in a fast-paced environment.
10. · Certifications/Additional Training – Nice-to-Have:
11. o Relevant certifications (e.g., Azure DevOps, Azure ML, ISTQB, Google Cloud Professional Data Engineer or Professional Cloud Developer) are a plus.
12. o Experience working with data governance tools such as Azure Purview and ensuring data compliance

Position: Backup Data ETL Developer

Experience: 6–9 Years

Location:Mumbai

Employment Type: Full-time

Job Description:

We are looking for a Backup Data ETL Developer with 6–9 years of experience in designing, developing, and supporting data extraction, transformation, and loading (ETL) processes.

The candidate should have strong hands-on experience with Hadoop, Spark, Informatica, and Snowflake, along with expertise in large-scale data processing and data integration technologies.

Key Skills:

Hadoop

Spark

Informatica

Snowflake

ETL Development

Data Integration

Data Transformation

Large-Scale Data Processing

ETL Workflows and Data Pipelines

Troubleshooting and Problem-Solving

Strong analytical and collaboration skills

Data Engineer Short Hiring Post

🚨 Hiring: Data Engineer

🔹 Experience: 5–9 Years

🔹 Location: Bangalore / Hyderabad

🔹 Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling

🔹 Process: L1 Virtual → L2 F2F Karat Test

🔹 F2F: Bangalore / Hyderabad Location

🔹 Positions: Immediate requirement

⚠️ Note: Candidates must be available for F2F Karat immediately after L1.

#Hiring #DataEngineer #PySpark #Python #SQL #BangaloreJobs #HyderabadJobs #Mphasis #ImmediateJoiners

Hiring: ETL Developer – Hadoop & PySpark

Location: Bangalore

Experience: 6–10 Years

Budget: 25–30 LPA

Work Mode: Weekdays

Job Description

We are looking for an experienced ETL Developer with strong expertise in Hadoop, PySpark, Python, and SQL to design, develop, and optimize data processing and transformation solutions. The ideal candidate should have hands-on experience working with big data technologies, building scalable ETL pipelines, and managing data for data warehousing and analytics.

Key Responsibilities

• Design, develop, and maintain scalable ETL pipelines for large-scale data processing.
• Develop data transformation workflows using PySpark and Python.
• Work with Hadoop and other big data technologies to process and manage large datasets.
• Write complex SQL queries for data extraction, transformation, validation, and analysis.
• Implement data cleansing, data quality checks, and data validation processes.
• Develop and optimize data integration workflows for data warehousing solutions.
• Troubleshoot ETL failures, performance issues, and data discrepancies.
• Optimize PySpark jobs and SQL queries for performance and scalability.
• Collaborate with data engineers, architects, analysts, and other stakeholders to deliver reliable data solutions.
• Ensure data accuracy, consistency, and adherence to established data governance standards.

Mandatory Skills

• Strong hands-on experience in ETL development.
• Good experience with Hadoop and big data technologies.
• Proficiency in PySpark and Python programming.
• Strong SQL skills, including complex queries and data manipulation.
• Experience in data processing, data transformation, and data integration.
• Understanding of data warehousing concepts and architecture.
• Experience in developing, debugging, and optimizing ETL pipelines.

Required Experience

• 6–10 years of relevant experience in ETL development and data engineering.
• Practical experience handling large datasets using Hadoop and PySpark.
• Strong analytical, problem-solving, and troubleshooting skills.
• Ability to work independently and collaborate effectively within a team.

Interested candidates can share their updated resumes along with current CTC, expected CTC, notice period, and total relevant experience.