Engineer III – Cloud Data Engineer
| Company | St. Jude Children’s Research Hospital |
|---|---|
| Location | Remote in USA, Memphis, TN, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Senior |
Requirements
- Proficiency in SQL for development and analysis.
- Expertise in dimensional data modeling, data warehousing, and big data pipeline optimization.
- Hands-on experience with AWS core services (e.g., AppFlow, Redshift, S3, Glue, IAM, Athena, Lambda, Step Functions, DMS, CloudWatch).
- Strong knowledge of API integration and ETL/ELT processes within a data lake ecosystem (e.g., AWS Lambda, Mulesoft, SSIS, PySpark, Confluent).
- DevOps experience with CI/CD processes, database source control (e.g., Liquibase, DB Up, SSDT, BitBucket, Flyway), and deployment techniques.
- Familiarity with big data tools, relational/NoSQL databases, and workflow management tools (e.g., Kafka, Spark, MongoDB, DynamoDB, SQL Server, Airflow, Luigi, Azkaban).
- Understanding of stream-processing systems and object-oriented scripting languages (e.g., Spark-Streaming, Kafka Streams, Scala, C++, Java, Python).
- Bachelor’s Degree with 5-8 years of experience in designing and implementing Infrastructure Architecture for enterprise-grade applications.
- Excellent communication, interpersonal, and organizational skills. Highly self-motivated with strong customer service orientation and team collaboration experience.
Responsibilities
- Develop and maintain data processing software, dimensional data modeling, big data pipelines, transformations, and related databases using AWS services (e.g., Redshift, S3, Glue, Athena, Lambda) and complementary tools and languages (e.g., Kafka, Spark, Airflow, Python, dbt, CData).
- Lead the design and development of cloud-native architectures, promoting the adoption of AWS services (e.g., RDS, EMR, EC2, DMS) and hybrid strategies for on-premise-to-cloud migrations, including phased cutovers and parallel environments.
- Provide strategic guidance to Data & Analytics teams, Data Science teams, IT leadership, and business partners on cloud architecture benefits, data protection, capabilities, scalability, and infrastructure needs.
- Build and optimize large datasets and big data pipelines to support self-service analytics, data science use cases, and performance metrics (e.g., operational efficiency, donor acquisition, time-to-insight).
- Act as a lead to Data Engineer I and II, providing training, mentoring, and knowledge transfer on current and target-state data platforms, standard operating procedures (SOPs), and best practices.
- Advise and prototype software, infrastructure, and data engineering delivery through automation, incorporating testing, quality assurance, compliance, and data protection measures for cloud, hybrid, and on-premise workloads.
- Partner with data, design, product, leadership, and IT teams to resolve complex technical issues, align with enterprise strategies (e.g., Office365, mobility, unified communications), and enhance data availability for customer insights.
- Identify and mitigate risks to data strategy, privacy, and sustainability, ensuring compliance-aware applications using AWS security services (e.g., IAM, CloudWatch, CloudTrail, KMS, Cyberark).
- Research emerging technologies, industry trends, and market developments to support product/process/data innovation and operational support activities.
- Distill and communicate the value of cloud-enabled tools and architectures to audiences of all technical depth, producing written recommendations and insights for senior leadership.
Preferred Qualifications
- Experience with dbt, Apache Airflow, CData, SageMaker, SQL Server 2019+, and security frameworks/patterns.
- Knowledge of additional AWS services (e.g., CloudTrail, DynamoDB, Parameter Store/Secrets Manager, EMR, AppFlow, SQS, SNS, Kinesis, KMS).
- Background in migrating on-premise SQL Server to AWS and managing VPC configurations.
- Experience with cost management and optimization within the AWS ecosystem.