Senior ETL & Cloud Engineer

Role Summary

As a Senior ETL & Cloud Engineer, you will handle  Solventum’s data movement and cloud foundations—designing resilient pipelines, enforcing data contracts and observability, and engineering secure, scalable AWS infrastructure. You will partner with product/analytics/security and deliver trustworthy, timely, and compliant data for clinical operations and analytics.

Key Responsibilities

Data & ELT/ETL Engineering

• Own source→raw→refined→curated pipelines using Python/PySpark on AWS and other clouds
• Design ELT with dbt (models, tests, docs); define conventions for staging/marts/semantic layers and automated tests to keep curated datasets trustworthy.
• Establish standards for data quality, observability (logs/metrics/alerts), SLAs/SLOs, and cost/performance (partitioning, clustering/Z‑order, warehouse sizing); author runbooks and drive incident response.
• BI tools knowledge is desirable

Cloud/Platform Engineering

• Design multi‑account AWS foundations: VPC networking, IAM least‑privilege roles/policies, private endpoints, and encryption with KMS.
• Build Infrastructure as Code with Terraform (or CloudFormation/AWS CDK); implement CI/CD for applications and infrastructure with policy guardrails.
• Engineer compute patterns across EKS/ECS and serverless (Lambda/EventBridge/SQS/SNS); enable blue/green or canary deployments.
• Implement observability with CloudWatch/CloudTrail/OpenSearch/Prometheus; publish actionable dashboards and alerts; participate in on‑call rotations.
• Design resilience (multi‑AZ/Region) with tested backup/DR and failover runbooks; optimize cost via tagging, rightsizing, and storage tiering.

Architecture, Enablement & Collaboration

• Drive architecture decisions (table formats, storage layout, CDC, streaming vs. batch) aligned to reference designs and retention policies.
• Curate reusable patterns
• Partner with product/analysts/InfoSec to translate requirements into robust data flows and clearly documented data contracts and usage guidance.

Minimum Qualifications

• Bachelor’s degree in CS/IS/Engineering or High School Diploma/GED with 9+ years of professional data engineering/ETL experience.
• 6+ years designing, building, and operating production ETL/ELT pipelines using Python (preferably PySpark) and SQL.
• 4+ years with Solventum’s primary data stacks: AWS (S3, Glue, Redshift) or Snowflake + dbt for ELT, orchestrated by Airflow.
• 3+ years hands‑on AWS across compute/networking/storage/security (e.g., EC2/EKS/ECS/Lambda, VPC, S3, RDS/Aurora, IAM, API Gateway).
• 3+ years with Infrastructure as Code (Terraform preferred; CloudFormation/AWS CDK acceptable) and CI/CD for apps and infra; practical observability experience.

Preferred Qualifications

• Spark & SQL performance tuning (partitioning/file sizing, broadcast, Z‑order/clustering, warehouse sizing).
• Data modeling (dimensional, Data Vault), contract‑first design, curated datasets with clear SLOs.
• Streaming/CDC (Kinesis/Kafka) and schema‑evolution strategies.
• Security‑by‑design (secrets management, access controls, encryption, retention/lifecycle).
• Healthcare standards (HL7 v2.x, FHIR); AWS/dbt/Snowflake certifications.