Analytica is looking for an experienced ETL Data Engineer to design, build, optimize, and support scalable data pipelines using Informatica and AWS. You’ll work closely with data architects, analysts, and business stakeholders to ensure reliable, secure, and high-quality data delivery across enterprise systems.
This role is ideal for someone who enjoys solving data integration challenges, improving performance and reliability, and contributing to modern cloud-based data platforms.
This role is a remote opportunity.
Analytica has been recognized by Inc. for 3 consecutive years as one of the 250 fastest growing business. We offer competitive compensation with opportunities for bonuses, employer paid health care, training and development funds, and 401k match.
Key Responsibilities:
Design, develop, and maintain ETL workflows using Informatica (PowerCenter and/or IICS)
Build and optimize cloud-based data pipelines and integrations on AWS
Develop and support ingestion, transformation, and loading processes from multiple source systems (SQL, APIs, flat files, etc.)
Implement and maintain data quality, validation, and reconciliation checks
Manage scheduling, dependencies, and monitoring of ETL jobs; troubleshoot failures and performance issues
Collaborate with data architects to implement target models in data lakes/warehouses
Ensure pipelines follow security, governance, and compliance standards
Contribute to best practices for CI/CD, version control, environment promotion, and deployment automation
Document ETL design, mappings, lineage, and operational processes
Participate in on-call or production support rotations as needed
Required Qualifications:
7+ years of hands-on ETL/data engineering experience
Strong experience with Informatica PowerCenter and/or Informatica Intelligent Cloud Services (IICS)
Experience building data solutions in AWS, including services such as:
S3, IAM, CloudWatch
Glue, Lambda, Step Functions
Redshift, RDS, or Aurora
Strong SQL skills (query optimization, joins, windowing, performance tuning)
Python scripting for automation or integration support
Experience with data warehouse concepts and dimensional modeling
Familiarity with SDLC practices and version control tools (Git, Bitbucket, etc.)
Ability to troubleshoot pipeline failures and performance bottlenecks independently
Strong communication skills and comfort working cross-functionally
Preferred Qualifications (Nice to Have):
Experience with Informatica Cloud connectors and Cloud Data Integration patterns
Exposure to Databricks or modern lakehouse platforms
CI/CD pipeline experience (Jenkins, GitHub Actions, Azure DevOps, etc.)
Experience with metadata management, lineage, and governance tools
Familiarity with Agile/Scrum methodologies