1 month ago
Detroit, MI, USASenior
Base Salary
$80k - $110k/yr
Responsibilities
- Design, develop, and maintain batch and near-real-time data pipelines using Snowflake, AWS services, and Python.
- Build and optimize Snowflake data models, including dimensional models, data vaults, and curated data marts.
- Develop, maintain, migrate, and modernize Python and IBM DataStage ETL/ELT workflows.
- Design and manage Control-M scheduling, dependencies, calendars, SLAs, monitoring, alerting, retries, and incident handling.
- Maintain data quality, governance, lineage, documentation, and validation standards across pipelines.
- Perform Snowflake and AWS performance tuning and cost optimization, including query optimization, clustering, warehouse sizing, and storage management.
- Partner with Data Science/AI, BI, Product, Platform, engineering, and business stakeholders to deliver data products and AI-ready datasets.
- Participate in estimation, planning, sprint execution, SDLC processes, and change management.
- Troubleshoot production issues, conduct root-cause analysis, and implement preventative improvements.
Requirements
- Strong hands-on expertise with Snowflake architecture, SQL development, performance tuning, security and roles, data loading and unloading, and best practices.
- Hands-on experience with the AWS data ecosystem, including services such as S3, IAM, CloudWatch, Glue, Lambda, EC2, Step Functions, EMR, or Kinesis.
- Strong Python programming experience for data engineering, including ETL/ELT frameworks, API ingestion, automation, unit testing, and logging.
- Experience designing and managing Control-M enterprise scheduling, dependencies, calendars, SLAs, monitoring, and incident handling.
- Solid experience building and maintaining IBM DataStage jobs, complex transformations, and production workloads.
- Advanced SQL skills for transformations, optimization, and data validation across large datasets.
- Experience with Git and CI/CD practices for data pipelines.
- Experience with monitoring, alerting, and production support in a 24x7 or business-critical environment.
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- At least 9 years of data engineering experience, including enterprise-grade data platform delivery and production support.
- Preferred experience includes AI/ML pipelines or feature datasets, ML lifecycle concepts, feature engineering, MLOps tools or processes, data governance and metadata tools, and streaming or event-driven architectures.
- Strong Agile/Scrum, communication, cross-team coordination, ownership, problem-solving, and attention-to-detail skills.
Benefits
- The employer is unable to sponsor or take over sponsorship of an employment visa at this time.
- The role operates in an Agile/Scrum delivery model and supports business-critical production environments.
About Infosys
Infosys is a public IT services and consulting company that builds and runs software systems for large enterprises across industries. It provides consulting, systems integration, cloud and AI services, engineering, and business process outsourcing, and sells platforms such as EdgeVerve's Finacle core banking suite. Founded in 1981 and headquartered in Bangalore, it serves clients in 50+ countries and is listed on the NSE, BSE, and NYSE.