Informatica ETL Developer - 6326296

Accenture•Morristown, NJ

3d•$44 - $54•Hybrid

About The Position

Accenture Flex offers you the flexibility of local fixed-duration project-based work powered by Accenture, a leading global professional services company. Accenture is consistently recognized on FORTUNE's 100 Best Companies to Work For and Diversity Inc's Top 50 Companies For Diversity lists. As an Accenture Flex employee, you will apply your skills and experience to help drive business transformation for leading organizations and communities. In addition to delivering innovative solutions for Accenture's clients, you will work with a highly skilled, diverse network of people across Accenture businesses who are using the latest emerging technologies to address today's biggest business challenges. You will receive competitive rewards and access to benefits programs and world-class learning resources. Accenture Flex employees work in their local metro area onsite at the project, significantly reducing and/or eliminating the demands to travel. As an ETL Data Engineer, you will be responsible for designing, developing, and maintaining data solutions that support data generation, collection, and processing. Your day-to-day activities will include creating data pipelines, ensuring data quality, and implementing extract, transform and load processes to migrate and deploy data across various systems. You are expected to be a subject matter expert, collaborate and manage the team to perform effectively, take responsibility for team decisions, engage with multiple teams, contribute to key decisions, and provide solutions to problems within your immediate team and across multiple teams. Develop and optimize scalable data pipelines to support complex data workflows and business requirements. Collaborate with cross-functional teams to integrate data solutions and ensure seamless data flow across platforms. Analyze and troubleshoot data issues, implementing robust solutions to maintain data integrity and performance. Support and mentor less experienced colleagues by sharing knowledge and best practices in data engineering. Contribute to the continuous improvement of data architecture and processes to enhance overall efficiency and quality.

Requirements

5+ years' work experience
Experience in Informatica PowerCenter, ETL development, data warehousing, and enterprise data integration
Expertise in Oracle SQL PLSQL, Unix shell scripting, performance tuning, and production support
Strong experience in developing ETL workflows, mappings, transformations, and data migration solutions
Expertise in data validation, reconciliation, troubleshooting, and optimization of large scale ETL processes
4+ years of experience in Python and Hadoop technologies including Hive, Spark, and HDFS
3+ years of experience in Autosys Control M job scheduling and monitoring
Experience working in Agile Scrum environments with end-to-end SDLC involvement
Knowledge of Git Bitbucket version control and release management processes
Strong analytical, problem solving, and stakeholder communication skills
60% onsite client work (3 days per week) in Charlotte, NC or Jersey City, NJ
High School Diploma or GED

Nice To Haves

Advanced proficiency in Informatica Intelligent Cloud Services
Advanced proficiency in Unix Shell Scripting, Agile Fundamentals, and Python (Programming Language)
Associate or bachelor's Degree

Responsibilities

Designing, developing, and maintaining data solutions that support data generation, collection, and processing.
Creating data pipelines, ensuring data quality, and implementing extract, transform and load processes to migrate and deploy data across various systems.
Developing and optimizing scalable data pipelines to support complex data workflows and business requirements.
Collaborating with cross-functional teams to integrate data solutions and ensure seamless data flow across platforms.
Analyzing and troubleshooting data issues, implementing robust solutions to maintain data integrity and performance.
Supporting and mentoring less experienced colleagues by sharing knowledge and best practices in data engineering.
Contributing to the continuous improvement of data architecture and processes to enhance overall efficiency and quality.