ETL Developer

Job Description:

Skill Set

Informatica, IDMC, Informatica MDM

Experience

4-6 Years

Location

Faridabad, Haryana, India

Work Mode- Hybrid

Job Description

Roles & Responsibilities

• Lead project team members through all activities required to successfully deliver Informatica.
• Define technical specifications for workflows and business rules.
• Prepare detailed design documents for data migration.
• Configure, build and unit test Informatica components, including data structures, roles, workflows, and portals.
• Train and mentor colleagues in Informatica implementation activities and best practices.
• Support integration, system, and user acceptance testing.
• Accountable for the Master Data Management, Technical Architecture, providing data modeling solutions and recommendations.
• Profile & Analyze Source Data usage using ETL tool.
• Automation, job scheduling, dependencies, monitoring.
• Configure/Script Business rules and transformation rules in ETL
• Data pipeline using IICS
• Hands on experience in Informatica MFT, Data Exchange (DX),and Data Transform (DT) modules
• Integration experience using various adapters (MLLP, SOAP, REST, SFTP, ODBC) will be essential.
• Strong knowledge and experience with developing complex SQL Queries, stored procedures, and triggers for RDBMS systems.
• Experience in administering, supporting, and performance tuning using Informatica.

Responsibilities

Design and execute ETL test scenarios, test cases and test scripts based on business and technical requirements.

Validate source-to-target data mapping, transformation rules, business rules and data flows.

Perform ETL, Data Warehouse and Database Testing across multiple data sources and target systems.

Validate data extraction, transformation, loading and reconciliation processes.

Perform data validation, data completeness, data accuracy and data integrity testing.

Write complex SQL queries for backend data validation, reconciliation and defect analysis.

Validate source-to-target mappings and identify data discrepancies. Perform database testing involving joins, stored procedures, views, functions, indexes and constraints.

Test incremental loads, full loads, CDC and batch processing where applicable.

Validate ETL workflows, schedules, dependencies and error-handling mechanisms.

Perform data reconciliation between source and target systems and investigate mismatches.

Validate duplicate records, missing records, null values, data truncation and transformation errors.

Execute regression, integration, system and end-to-end testing for ETL/data pipelines.

Validate large-volume datasets and perform data quality and consistency checks.

Work with developers, data engineers, business analysts and product teams to resolve data-related issues.

Analyze ETL job failures and assist development teams with root-cause analysis (RCA). Log, track and manage defects using tools such as Jira, Azure DevOps or similar.

Prepare test execution reports, defect reports and testing status updates.

Participate in requirement analysis, test planning, estimation and defect triage meetings.

Support UAT, production validation and post-release data verification.

Ensure testing complies with enterprise data governance, security, privacy and quality standards.

Work in an Agile/Scrum environment and participate in sprint planning, daily stand-ups, reviews and retrospectives.

Collaborate with globally distributed teams and stakeholders across business and technology functions.

Understand insurance-domain data such as policy, customer, claims, billing, premium and financial data is an advantage.

Requirements

4–6 years of hands-on experience in ETL Testing / Data Warehouse Testing / Database Testing.

Strong understanding of ETL concepts, data warehousing and data integration processes.

Strong hands-on SQL skills including complex joins, subqueries, CTEs, aggregations and data reconciliation queries.

Experience with ETL tools such as Informatica, IBM DataStage, SSIS, Talend, Azure Data Factory or similar.

Experience testing large-volume data and enterprise data pipelines. Good understanding of Dimensional Data Modeling, Star Schema, Snowflake Schema, Fact and Dimension tables.

Strong knowledge of source-to-target mapping and transformation validation.

Experience with Oracle, SQL Server, DB2, PostgreSQL or other relational databases.

Knowledge of batch processing, scheduling, incremental/full loads and data migration testing.

Experience with API, web service or downstream application data validation is preferred.

Good understanding of SDLC, STLC, defect lifecycle and Agile methodologies.

Experience with Jira, Azure DevOps, ALM or similar test/defect management tools.

Exposure to cloud data platforms such as Azure/AWS is an added advantage.

Exposure to Python or scripting for test-data validation/automation is desirable.

Knowledge of data quality, reconciliation, data lineage and data governance.

Strong analytical and problem-solving skills with the ability to investigate complex data issues.

Excellent communication and stakeholder-management skills.

Prior experience in Insurance, BFSI or other regulated enterprise environments will be highly preferred.

Strong Senior Developer – PL/SQL, SQL & ETL (Microsoft SSIS) Profile

2

Mandatory (Experience 1) – Must have minimum 5+ years of strong hands-on experience in PL/SQL and SQL development, including complex stored procedures, functions, queries, joins, data manipulation, and query/performance optimization.

3

Mandatory (Experience 2) – Must have strong hands-on experience in ETL development using Microsoft SSIS, including building, maintaining, optimizing, and troubleshooting SSIS packages for large-volume data movement and transformation.

4

Mandatory (Experience 3) – Must have solid experience working with Data Warehousing concepts and architectures, including data models, fact/dimension structures, ETL data flows, and enterprise reporting/data warehouse environments.

5

Mandatory (Experience 4) – Must have experience managing batch jobs, scheduling, and data pipelines, ensuring timely and reliable execution of enterprise ETL workflows.

6

Mandatory (Experience 5) – Must have hands-on experience in production support for SSIS/ETL and data warehouse jobs, including monitoring job execution, troubleshooting failures, performing root cause analysis, and implementing preventive fixes.

7

Mandatory (Experience 6) – Must have experience with data quality, validation, and troubleshooting, including identifying and resolving data discrepancies/issues affecting downstream reports, dashboards, and analytics.

8

Mandatory (Experience 7) – Must have experience with unit, integration, and regression testing of SQL, PL/SQL, and ETL components, along with strong documentation of technical designs, data mappings, data flows, and deployment processes.

9

Mandatory (Location) – Must be willing to work in a hybrid model from a city where Cognizant has an office.

10

Mandatory (Notice Period) – Immediate joiners or candidates who can join within 2–4 weeks.

Hiring: Informatica IDMC / IICS Developer

Location: Faridabad, Haryana

Experience: 4–7 Years

Must-Have:

• Informatica IDMC / IICS

• Data Integration & Application Integration (CAI)

• ETL / Data Pipelines / Data Migration

• REST, SOAP, SFTP & API Integration

• Strong SQL, Stored Procedures & RDBMS

• Job Scheduling, Monitoring & Performance Tuning

Good to Have: Informatica MFT, DX, DT, MDM & Data Quality

About AuxoAI:

AuxoAI is a global platform-based services firm. We help companies—turn their strategies into practical digital and AI solutions. By understanding how our clients make decisions, we use digital and Artificial Intelligence (AI) technologies to drive growth, enhance their operations, improve customer experiences, and provide clear, actionable insights from their data. What We Do We work across various industries such as healthcare, high-tech, consumer packaged goods (CPG), finance etc., and in sales, marketing, and customer support functions.

We help our clients with accelerating their digital and AI journeys through:

• AI Application Development

• Data, Digital and Cloud acceleration using AI

• AI Native Product Engineering

We are seeking a skilled and experienced Data Engineer to join our dynamic team. The ideal candidate will have 6+ years of prior experience in data engineering, with a strong background in AWS (Amazon Web Services) technologies. This role offers an exciting opportunity to work on diverse projects, collaborating with cross-functional teams to design, build, and optimize data pipelines and infrastructure.

Responsibilities:

* Design, develop, and maintain scalable data pipelines and ETL processes leveraging AWS services such as S3, Glue, EMR, Lambda, and Redshift.

* Collaborate with data scientists and analysts to understand data requirements and implement solutions that support analytics and machine learning initiatives.

* Optimize data storage and retrieval mechanisms to ensure performance, reliability, and cost-effectiveness.

* Implement data governance and security best practices to ensure compliance and data integrity.

* Troubleshoot and debug data pipeline issues, providing timely resolution and proactive monitoring.

* Stay abreast of emerging technologies and industry trends, recommending innovative solutions to enhance data engineering capabilities.

Requirements :

* Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

* 6+ years of prior experience in data engineering, with a focus on designing and building data pipelines.

* Proficiency in AWS services, particularly S3, Glue, EMR, Lambda, and Redshift.

* Strong programming skills in languages such as Python, Java, or Scala.

* Experience with SQL and NoSQL databases, data warehousing concepts, and big data technologies.

* Familiarity with containerization technologies (e.g., Docker, Kubernetes) and orchestration tools (e.g., Apache Airflow) is a plus.

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

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

We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate should have strong expertise in SQL, Python, Linux, and modern data engineering practices to support data integration, transformation, and analytics.

Key Responsibilities

• Design, develop, and maintain ETL/ELT data pipelines.
• Write efficient and optimized SQL queries for data extraction, transformation, and reporting.
• Develop automation scripts using Python for data processing and workflow optimization.
• Work with Linux environments for deployment, monitoring, and troubleshooting.
• Ensure data quality, integrity, and reliability across data platforms.
• Collaborate with data analysts, software engineers, and business stakeholders to deliver data solutions.
• Monitor, troubleshoot, and optimize data pipelines for performance and scalability.
• Implement best practices for data security, governance, and documentation.

Required Skills

• Strong experience in Data Engineering concepts and ETL/ELT processes.
• Proficiency in SQL, including query optimization and database design.
• Strong programming skills in Python.
• Hands-on experience with Linux commands, shell scripting, and system administration basics.
• Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
• Familiarity with Git/version control.
• Strong analytical and problem-solving skills.

Preferred Skills

• Experience with cloud platforms (AWS, Azure, or GCP).
• Knowledge of Apache Spark, Airflow, Kafka, or similar data engineering tools.
• Experience with data warehousing solutions and big data technologies.
• Understanding of CI/CD pipelines and containerization (Docker/Kubernetes).

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• Relevant certifications in cloud or data engineering are an added advantage.

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.

• Design, build, and maintain scalable ETL/ELT pipelines for batch and real-time data ingestion and transformation.
• Develop and optimize data lake and data warehouse architectures (e.g., Snowflake, BigQuery, Redshift).
• Work with cloud platforms GCP, Azure to manage data infrastructure.
• GCP as mandatory skills
• Collaborate with analytics and product teams to understand data needs and deliver solutions.
• Ensure data quality, reliability, security, and compliance across all data systems.
• Mentor junior data engineers and contribute to best practices and code reviews.
• Monitor and troubleshoot data pipeline performance and resolve data-related issues.
• Automate data validation, monitoring, and alerting processes.
• 8+ years of experience in data engineering or software engineering with a data focus.
• Proficient in SQL and at least one programming language (e.g., Python, Scala, Java).
• Experience with modern data warehousing tools (e.g., Snowflake, Redshift, BigQuery).
• Strong understanding of data modeling, data lakes, and ETL/ELT design.
• Hands-on experience with orchestration tools like Airflow, dbt, or similar.
• Solid experience with cloud data platforms (AWS/GCP/Azure).
• Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), and version control (Git).
• Experience working in a DevOps or DataOps environment.
• Knowledge of data governance, lineage, and cataloging tools (e.g., Collibra, Alation).
• Familiarity with streaming technologies (Kafka, Spark Streaming, Flink).
• Experience supporting machine learning workflows and data science initiatives.