- Company Name
- Talent Groups
- Job Title
- AWS Data Solutions Engineer
- Job Description
-
**Job Title**
Senior AWS Data Solutions Engineer
**Role Summary**
Lead the design, development, and deployment of scalable, high‑performance data solutions on AWS. Own the end‑to‑end SDLC for data pipelines, architecture, and EHR data integration, leveraging Databricks, Elastic Search, and advanced analytics tools. Deliver secure, efficient, and innovative data services in an agile, cross‑functional environment.
**Expectations**
- 12+ years of experience building complex database systems.
- 8+ years hands‑on with Databricks, Elastic Search/Kibana, Python/Scala, and Oracle databases.
- 5+ years of ETL development, data warehousing, and data‑visualization.
- 5+ years of AWS cloud development and deployment.
- Proven application of CMM/CMMI Level‑3 practices and agile, test‑driven development.
- Comfort with Azure DevOps CI/CD pipelines (preferred).
**Key Responsibilities**
1. Architect and implement data solutions: data lakes, warehouses, real‑time pipelines, and EHR HL7 integrations.
2. Develop, test, and maintain ETL/ELT processes using PySpark, Scala, and Python.
3. Build and tune Databricks workloads; manage cluster provisioning, job scheduling, and cost optimization.
4. Design and operate Elastic Search/Kibana clusters for metadata search and analytics.
5. Create and enforce data integrity frameworks, security policies, and compliance controls.
6. Deploy infrastructure as code (AWS CloudFormation, Terraform) and CI/CD pipelines (Azure DevOps, GitHub Actions).
7. Collaborate with data scientists, analysts, and business stakeholders to translate requirements into technical solutions.
8. Document architecture, procedures, and best practices; mentor junior engineering staff.
**Required Skills**
- Expertise in AWS services (S3, EMR, Glue, Redshift, Athena, Lambda, etc.).
- Advanced knowledge of Databricks, Spark, PySpark, Scala.
- Elastic Search/Kibana administration and query optimization.
- Oracle database development and tuning.
- Python and/or Scala programming for data engineering.
- ETL and data pipeline design (Airflow, Prefect, etc.).
- Data warehousing concepts and implementation (Redshift, Snowflake, etc.).
- Data visualization tools (Tableau, Power BI) and reporting.
- CMM/CMMI Level‑3 methodology and agile, test‑driven development.
- CI/CD pipeline management (Azure DevOps, GitHub Actions, Jenkins).
- Strong problem‑solving, communication, and documentation skills.
**Required Education & Certifications**
- Bachelor’s degree in Computer Science, Computer Engineering, or a related field.
- AWS Certified Solutions Architect – Professional or equivalent AWS certification (preferred).
- Databricks Certified Data Engineer – Associate (preferred).
---