Cloud Data Engineer
My client is one of the world’s leading executive search consulting firms. They are currently seeking a Cloud Data Engineer to join their team. The successful candidate will become part of a team focused on cloud data architecture and will be responsible for solution architecture, implementation, IaC and support.
Apply for the Cloud Data Engineer role above or contact John Egan for more information.
Responsibilities of the Cloud Data Engineer role:
- Implement solutions using Infrastructure as Code to ensure repeatable, consistent, and deterministic outcomes. Develop fully automated solutions using AWS Cloud Native Services that enable performance and cost optimized solutions.
- Developing / Debugging ETLs using Python & PySpark as well as developing Redshift queries.
- Partner with development and build release teams on data initiatives.
- Rapidly developing prototype data pipelines to validate solutions.
- POC code and developing it into a production ready solution with a focus on code quality, testing, security, performance and operational excellence.
- Embrace DevOps practices / CALMS principles
- Contribute to the evolution of the overall Analytics architectural strategy, including Reference Architectures and Reference Implementations to grow the platform.
- Contribute to the adoption of the firm’s Data Platform and work with stakeholders to enable them to self-serve in their consumption of the platform
- Partner with Data Scientist, Analysts, Architects, and Engineers to build Solution Architectures that leverage the Data Platform in an optimized, low barrier to entry manner.
- Identify and implement processes, tools, and methods that support the target strategy, address data lifecycle, cover data movement, data security, data privacy, and metadata management.
- Effectively communicate new recommendations and solutions to peers, with an emphasis on knowledge sharing. Communicate architectural information to non-technical audiences.
- Adapt existing design patterns and reference architectures specifically for the Spencer Stuart environment.
Required Skills and Experience for the Cloud Data Engineer role:
- Self-starter / autonomy is a must.
- Demonstrated ability to self-teach, learn, and apply learnings as a regular course of activity.
- 4+ years Solution Architecture experience, including 2+ years Data Architecture.
- Hands-on experience with several of the following AWS services (Athena, Glue ETL/Catalog, Redshift, DynamoDB, AWS Lambda, CLI, EC2).
- 3+ years hands-on AWS experience, including 2+ years hands-on AWS experience in CodePipeline and/or CloudFormation.
- Strong DevOps mindset and experience in promoting code from staging to production environments through automation.
- 3+ years Software Development experience, including 2+ years of Python (including Spark) experience.
- Experience building & operating data lakes and data warehouse solutions preferably on AWS.
- BA/BS degree in Computer Science, related Software Engineering or equivalent experience.
- AWS Certified, preferably Big Data, SA and/or DevOps.
- A well-grounded knowledge of engineering and continuous delivery practices using modern software development tooling (GitHub, CodeCommit, IDEA, PyCharm, Visual Studio, etc.), processes (e.g. Scrum, Agile), and toolsets (e.g. JIRA, Confluence).
- Understanding of IAM Security, Policies, and Roles.
Desirable Skills and Experience for the Cloud Data Engineer role:
- Data Science and Analytics programming language experience (ML, Python, R, etc.)
- Knowledge of big data technologies and frameworks (i.e. Kinesis, Hadoop, Hive, Kafka, etc.)
- Experience and/or demonstrated interest in RDS / Aurora, Route53, SQS, SNS and other new technology.
- Active in technical communities (e.g. AWS Meetups), & development of publications (e.g. SlideShare, Medium)
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