ETL Tester at Nuvento Systems · Remote only · 3 - 8 years · ₹8L - ₹15L / yr · Profitable · Remote only · Posted 17 Feb 2022

What roles and responsibilities will be performed by the selected candidate?
§ Should be able to handle all ETL Datawarehouse testing phases (Azure environment).
§ Should be able to test complex SQL scripts including Spark SQL
§ Should be able to apply business and functional knowledge including testing standards, guidelines, and testing
methodology to meet the teams overall test objectives.
§ Should be able to identify business requirements including data sources, target systems, transformations
required, business rules required to be applied and existing data model from the mapping document.
§ Define Testing strategy, Test approach, Test suites and Test cases.
§ Run, test and debug ETL jobs (Azure environment).
§ Identify and track defects to closure and keep defect log.
§ Should be able to produce test result documentation that are clear and concise along with documentation of
tests performed, test coverage, test risks, assumptions, issues, and dependencies.
§ Bringing in industry best practices in ETL Testing.
§ Should be able to test complex SQL scripts including Spark SQL
§ Should be able to test pandas data frame ETL transformations.
What is the expectation from the candidate’s current role/profile?
§ 2-5 years of experience in core ETL testing expertise with strong exposure to agile methodology.
§ Ability to apply business and functional knowledge, to define testing strategy, test approach and test case
design.
§ Should have excellent SQL skills
§ Should have worked on ETL project involving multiple layers/stages of database processing with various kinds
of sources/targets like files, Oracle, SQL Server, Webservices. Delta Lake etc…
§ Should have at least intermediate level knowledge of python scripting and pandas (Python data analysis
library).
§ Knowledge of Software Development Lifecycle including the functional and non-functional test phases
§ Good interpersonal, communication and organizational skills
§ The ability to work and team effectively with team and management personnel across

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Location: Bangalore Experience: 5 to 7 years Employment type: Full-time, permanent Work Hours: General Shift (10.00 AM to 7.00 PM) website: www.amazech.com Qualifications: Minimum B.E./B.Tech, or higher in Computer Science, Information Technology, Data Engineering, or a related field, with a good academic background. Key Responsibilities: • Design, develop, and maintain end-to-end data pipelines. • Build and optimize ETL/ELT processes for large-scale data processing. • Implement Azure-based data solutions ensuring scalability and performance. • Collaborate with stakeholders to understand business data requirements. • Perform performance tuning and optimization across data platforms. • Support production environments, conduct root cause analysis, and resolve data-related issues. • Maintain comprehensive technical documentation and structured knowledge transfer documents. • Work effectively within Agile/Scrum frameworks and contribute to sprint planning and delivery. • Ensure secure and compliant data handling using Azure best practices. Required Skills & Experience • End-to-end ETL/ELT pipeline development, integration, and performance optimization • Azure Synapse, Azure Logic Apps, Azure SQL, and Azure Databricks, with a strong focus on performance tuning • Microsoft Azure services, including Storage Accounts, Key Vault, and Cognitive Services • Advanced proficiency in Python development and modern productivity tools such as GitHub Copilot and Cursor • Strong documentation discipline, including technical design documentation, and structured knowledge transfer documents • Experience operating within Agile/Scrum frameworks, including production support, root cause analysis, and effective stakeholder collaboration
We are looking for a dynamic Data Engineer to join our team of technology enthusiasts. You will leverage data to drive strategic decision-making and pioneering solutions, working with complex datasets, collaborating closely with stakeholders, and transforming data into actionable insights to drive innovation.
Qualifications and Skills:
- Minimum 5 years of experience as a Data Engineer
- Hands-on experience with Azure cloud-based data solutions
- Expertise in database design and management, including SQL databases such as SQL Server
- Proficient in ETL (Extract, Transform, Load) design for data integration and processing
- Strong knowledge of data modeling principles and techniques
- Ability to analyze and translate data into actionable insights, reports, and visualizations
- Proficiency in Power BI for reporting and data visualization
Desirable Skills:
- Experience with Power BI Report Builder / Reporting Services
- Knowledge of statistical analysis or Data Science
- Experience within the UK Insurance industry is a plus
- Python or R coding skills
Responsibilities:
- Implement efficient data exchange between internal and external systems to increase efficiency and reduce re-keying and translation errors
- Support the Broking business by developing high-quality information resources, ensuring data availability and accessibility for decision-making
- Engineer data inputs and outputs from core applications and semi-structured remote service data through data syncs between data lake, ODS (SQL database), and leveraging Fabric and ADF
- Perform data engineering tasks including ingestion, cleansing, and collation from a wide range of internal and external sources
- Implement different methods of streaming data and create reconciliations for datasets
- Build analytical models to support reporting and analytics
- Collaborate with an agile delivery team to work on the backlog of specified work
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!
Location – Hyderabad (Hybrid)
Work Experience – 5 to 7 years
CTC – upto 20 LPA
Roles & Responsibilities:
· We are looking for a Senior Data Engineering who will be majorly responsible for designing, building and maintaining ETL/ ELT pipelines.
· Integration of data from multiple sources or vendors to provide the holistic insights from data.
· You are expected to build and manage Data warehouse solutions, designing data models, creating ETL processes, implementing data quality mechanisms etc.
· Performs EDA (exploratory data analysis) required to troubleshoot data related issues and assist in the resolution of data issues.
· Should have experience in client interaction.
· Experience in mentoring juniors and providing required guidance.
Required Technical Skills
· Extensive hands on experience in Python, Pyspark, SQL, Dataiku.
· Strong experience in Data Warehouse, ETL, Data Modelling, building ETL Pipelines, Snowflake database.
· Working knowledge in Databricks, Redshift, ADF etc.
· Hands-on experience in cloud services like Azure, AWS- S3, Glue, Lambda, CloudWatch, Athena.
· Sound knowledge in end-to-end Data management, Data ops, quality and data governance.
· Familiar with SFDC, Waterfall/ Agile methodology.
· Strong domain knowledge in Pharma domain/ life sciences commercial data operations.
Qualifications
· Bachelor’s or master’s Engineering/ MCA or equivalent degree.
· 5-7 years of relevant industry experience as Data Engineer.
· Experience working on Pharma syndicated data such as IQVIA, Veeva, Symphony; Claims, CRM, Sales etc.
· High motivation, good work ethic, maturity, self-organized and personal initiative.
· Ability to work collaboratively and providing the support to the team.
· Excellent written and verbal communication skills.
· Strong analytical and problem-solving skills.
Job Description
We are looking for an experienced ETL Developer with strong expertise in ETL development, Hadoop, PySpark, Python, and SQL. The candidate should have hands-on experience in developing data pipelines, processing and transforming large datasets, and working with data warehousing and big data technologies.
Key Responsibilities
- Design, develop, and maintain ETL processes and data pipelines.
- Work with Hadoop and PySpark to process and transform large volumes of data.
- Develop and optimize Python scripts for data processing and automation.
- Write complex SQL queries for data extraction, transformation, and validation.
- Perform data cleansing, integration, transformation, and validation.
- Work with data warehousing concepts and large-scale data processing systems.
- Optimize ETL workflows for performance, scalability, and reliability.
- Troubleshoot data pipeline failures and resolve data quality issues.
- Collaborate with data engineers, analysts, and other technical teams.
- Follow data governance, quality, and development best practices.
Required Skills
- Strong experience in ETL Development – Mandatory
- Hands-on experience with Hadoop – Mandatory
- Strong experience in PySpark – Mandatory
- Good programming skills in Python – Mandatory
- Strong knowledge of SQL – Mandatory
- Experience in Data Processing and Transformation – Mandatory
- Knowledge of Data Warehousing – Mandatory
- Experience with Big Data Technologies – Mandatory
Opportunity Details
Role: ETL Developer – Hadoop & PySpark
Experience: 6–10 Years
Location: Bangalore
Mandatory Skills
ETL Development | Hadoop | PySpark | Python | SQL | Data Processing & Transformation | Data Warehousing | Big Data Technologies
Job Title : Data / AI / GenAI – Engineering & Analytics
Experience : 4+ Years
Location : Noida / Gurugram / Ahmedabad
Employment Type : Full-time | On-site at client location
Working Days : 5 days per week
Working Hours : Standard business hours
Position Overview : We are seeking professionals to deliver modern data engineering, business intelligence, cloud analytics and AI-powered applications, according to their specialization.
Mandatory Skills :
Python, SQL, ETL/ELT, Data Engineering, Power BI, Azure Data Factory, Databricks, PySpark, Data Modeling, GenAI/LLMs, RAG, Vector Databases, AI Agents (as per role specialization).
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- Power BI Developers : Dashboards, DAX, Power Query, reporting and data modeling
- Azure Data Engineers : Azure Data Factory, Data Lake, Azure SQL and cloud pipelines
- Databricks Engineers : Apache Spark, PySpark, Delta Lake and scalable processing
- Data Engineers : ETL/ELT, SQL, Python, data warehousing and quality
- GenAI / RAG Engineers : LLMs, prompts, embeddings, vector databases and retrieval pipelines
- Agentic AI Engineers : AI agents, tool calling, orchestration and multi-agent workflows
Key Responsibilities :
- Design, develop and maintain data pipelines, analytics solutions or AI applications.
- Build and optimize data integration, transformation and processing workflows.
- Develop dashboards and analytical models for business decision-making.
- Use cloud data platforms and modern engineering frameworks.
- Develop and evaluate LLM applications, RAG solutions or AI agents as applicable.
- Ensure data quality, security, performance and reliability.
- Collaborate with engineering teams and stakeholders on testing, deployment and documentation.
Required Skills & Qualifications :
- Bachelor’s degree in Computer Science, IT, Data Science, Engineering or related discipline.
- 4–5 years of relevant experience in data, analytics, AI or software engineering.
- Hands-on expertise in at least one listed specialization; not all technologies are required.
- Relevant Python, SQL, DAX or other technical skills depending on the position.
- Understanding of cloud platforms, APIs, integration and software practices.
Preferred Qualifications :
- Azure, Databricks or Microsoft Fabric experience.
- For GenAI roles : Azure OpenAI, OpenAI APIs, LangChain, LlamaIndex or LangGraph.
- For relevant roles : vector databases, CI/CD, Docker, MLOps or LLMOps.
Note : Candidates are expected to have expertise in their relevant specialization, not in every listed technology or role.
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.
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
Technical Lead
Job Description
Role Overview
We are seeking a highly skilled Data Engineering Lead with minimum of 5 years of hands-on experience in Azure data engineering, data warehousing, and automation-driven integration. The ideal candidate should be a proven technical lead, capable of driving end-to-end
project delivery and working closely with customer teams. This is a Work from Office / Customer Site role.
Roles and Responsibilities
• Lead the design, development, and delivery of data engineering and automation projects.
• Architect and implement ETL/ELT pipelines using Azure Data Factory.
• Design and manage enterprise data warehouses including dimensional modeling and
schema optimization.
• Manage Azure components including Storage Accounts, Data Lakes, Azure SQL, and Synapse.
• Drive automation initiatives across data ingestion and transformation workflows.
• Collaborate with business and technical stakeholders to translate requirements into scalable solutions.
• Mentor team members and enforce engineering best practices.
• Serve as the technical anchor responsible for ensuring high-quality, on-time delivery.
Skills and Qualification
• Strong hands-on experience with Azure Data Factory, Azure Storage, Azure SQL/Synapse.
• Deep understanding of data warehousing concepts: star/snowflake schemas, fact/dimension modeling.
• Experience with automation-led data engineering solutions.
• Strong troubleshooting, optimization, and analytical skills.
• Excellent communication and stakeholder management abilities.
• Proven experience as a Technical Lead leading teams and delivery.
Must Have
• Min of 5 years of relevant data engineering experience.
• Strong Azure Data Engineering and Data Warehousing expertise.
• Proven Technical Lead experience.
• Ability to work from office and customer site.
• Strong ownership mindset with a focus on quality and delivery excellence.
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.













