Numeric Technologies - Senior Data Engineer

Key Responsibilities :

Data Engineering & Development :

- Design, develop, and maintain scalable data pipelines using Informatica IDMC/IICS and Databricks.

- Build and optimize ETL/ELT processes for data ingestion, transformation, validation, and delivery.

- Develop robust and reusable data integration frameworks to support enterprise analytics and reporting.

- Implement data processing workflows using SQL, Python, and Databricks technologies.

- Ensure efficient movement of data across multiple source and target systems.

Databricks & Big Data Engineering :

- Design and implement data solutions using Databricks Lakehouse architecture.

- Develop and optimize Spark-based data processing jobs within Databricks.

- Work with Delta Lake, Data Lakes, and modern cloud-based data architectures.

- Build scalable batch and near real-time data processing solutions.

- Optimize Databricks workloads for performance, scalability, and cost efficiency.

- Participate in platform modernization and cloud migration initiatives.

Informatica Cloud (IDMC/IICS) Development :

- Design and develop data integration solutions using Informatica Cloud services.

- Create mappings, mapping tasks, task flows, synchronization jobs, and data quality processes.

- Implement data governance, data validation, and metadata management practices.

- Troubleshoot and resolve Informatica workflow and performance-related issues.

- Support data migration and cloud integration initiatives.

Data Modeling & Database Engineering :

- Design and maintain conceptual, logical, and physical data models.

- Develop complex SQL and PL/SQL scripts, stored procedures, views, and database objects.

- Ensure adherence to enterprise data management standards.

- Improve database performance through indexing, partitioning, and query optimization.

- Support master data management and data governance initiatives.

CI/CD & Automation :

- Build and maintain CI/CD pipelines for data engineering deployments.

- Leverage Git, Jenkins, Azure DevOps, or similar tools for version control and automated releases.

- Implement automated testing and deployment processes for data workflows.

- Promote DevOps best practices within data engineering projects.

Performance Optimization & Troubleshooting :

- Analyze and optimize existing ETL workflows, SQL queries, and Databricks jobs.

- Reverse engineer legacy data systems and recommend modernization strategies.

- Identify bottlenecks and implement performance improvements across the data ecosystem.

- Monitor and troubleshoot production data pipelines and platform issues.

- Ensure high availability, reliability, and scalability of data solutions.

Stakeholder Collaboration :

- Work closely with Data Architects, Business Analysts, Product Teams, and Reporting Teams.

- Translate business requirements into scalable technical solutions.

- Participate in technical design discussions and solution reviews.

- Provide production support and technical guidance when required.

- Contribute to documentation, knowledge sharing, and best practices.

Required Skills & Experience :

Experience :

- 7+ years of overall experience in Data Engineering, ETL Development, and Data Integration.

- Proven experience delivering end-to-end enterprise data projects.

- Strong experience working in cloud-based data environments.

Technical Skills :

Advanced SQL & Database Expertise :

- Strong expertise in advanced SQL development and query optimization.

- Extensive experience with relational databases and data warehousing concepts.

- Strong PL/SQL development experience.

Data Modeling & Data Management :

- Expertise in dimensional modeling, star schema, snowflake schema, and data warehousing principles.

- Strong understanding of data governance, metadata management, and data quality practices.

Informatica Cloud (IDMC/IICS) :

- Minimum 3+ years of hands-on experience with Informatica Intelligent Data Management Cloud (IDMC) or Informatica Intelligent Cloud Services (IICS).

- Experience developing cloud-native integration solutions and ETL workflows.

- Strong knowledge of Informatica Cloud Data Integration components and services.

Databricks & Big Data :

- Minimum 3+ years of hands-on experience with Databricks.

- Strong understanding of Databricks architecture and Lakehouse concepts.

- Experience with Apache Spark, Delta Lake, and distributed data processing frameworks.

- Knowledge of Big Data ecosystems and cloud-based analytics platforms.

Python :

- Strong proficiency in Python for data engineering and automation.

- Experience developing data processing and transformation scripts.

- Familiarity with Python libraries used in data engineering workflows.

DevOps & CI/CD :

- Experience with Git, Jenkins, Azure DevOps, or similar tools.

- Knowledge of CI/CD implementation and release management processes.

- Familiarity with Infrastructure as Code and deployment automation is preferred.

Preferred Skills :

- Experience with AWS, Azure, or Google Cloud Platform.

- Exposure to data lake and modern data platform implementations.

- Experience working with large-scale enterprise data environments.

- Knowledge of data governance, security, and compliance frameworks.

- Familiarity with Agile/Scrum delivery methodologies.

Key Competencies :

- Strong ownership mindset with a proactive approach to problem-solving.

- Ability to independently manage complex technical assignments.

- Excellent analytical and troubleshooting skills.

- Strong communication and stakeholder management capabilities.

- Ability to work effectively in a fully remote and globally distributed environment.

- Focus on quality, performance optimization, and continuous improvement.

Educational Qualifications :

- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.

Why Join Us ?

- Opportunity to work on large-scale cloud data transformation initiatives.

- Exposure to modern data engineering technologies including Databricks and Informatica Cloud.

- Fully remote work environment with flexibility and autonomy.

- Collaborative, innovation-driven culture with strong career growth opportunities.

- Work on enterprise-grade analytics and data modernization projects.