Staff, Software Engineer

Responsibilities

• Design, build, and scale data pipelines to support enterprise reporting and analytics across large, complex datasets
• Lead architecture and implementation of modern data warehouse platforms (batch + real-time) to enable reliable, scalable reporting and BI use cases
• Drive adoption of best practices in data engineering, coding standards, and cloud infrastructure
• Partner with product, analytics, and engineering teams to deliver reliable data solutions
• Mentor engineers, conduct design/code reviews, and raise the technical bar across the team

Qualifications

• 8-13 years of experience in software/data engineering with proven track record of impact
• Strong expertise in Big Data ecosystems (Spark, Hadoop, etc)
• Proficiency in SQL, Python/Scala/Java for data processing
• Hands-on experience with cloud platforms (AWS preferred) EMR, Glue, S3, Lambda, etc
• Experience with data modeling, warehousing, and distributed systems
• Strong knowledge of enterprise DWH systems for reporting and analytics (e g, schema design, query optimization, BI integration)
• Deep understanding of scalability, performance optimization, and fault tolerance
• Strong problem-solving, debugging, and system design skills
• Good to Have: Experience with Redshift or other modern data warehouse platforms (e g, Snowflake, Databricks, BigQuery)
• Exposure to Greenplum or other MPP (Massively Parallel Processing) databases
• Exposure to ML/AI data pipelines or advanced analytics platforms
• Experience with CI/CD, Terraform, Kubernetes, Docker in data environments
• Knowledge of data governance, security, and compliance practices