Data Engineers develop modern data architecture approaches to meet key business objectives and provide end-to-end data solutions. You might spend a few weeks with a new client on a deep technical review or a complete organizational review, helping them to understand the potential that data brings to solve their most pressing problems. On other projects, you might be acting as the architect, leading the design of technical solutions, or perhaps overseeing a program inception to build a new product. It could also be a software delivery project where you're equally happy coding and tech-leading the team to implement the solution.
You’ll spend time on the following:
- Take the needs and challenges of a client and formulate the technical roadmap and technology solution that will support their business strategies and goals.
- Provide architectural recommendations, solution and approach given trade offs and ability to communicate that to the business.
- Quickly gain an understanding of the landscape of tools and data frameworks so as to recommend next steps, approach (such as real-time streaming, batch, workflows, etc.)
- Credentialize roadmap and architecture
- Enhance Data Engineering capability through coaching, mentoring and leadership
- Co-create and shape strategy and approach to engagements to achieve the desired business outcomes
- Collaborate with other Data Engineer Anchors in the org to learn and share best practices and techniques
- Provide technical leadership in an enterprise environment to ensure delivery of exceptional technical solutions.
- Mentor on approach and execution of solutions, coach on technologies and establishing a team-wide comprehension of solution capabilities and direction.
- Ensure technical expectations of deliverables are met.
- Drive Thought-Leadership on engineering and architectural practices and standards.
- Be an inspiration for innovation to the client.
- Become a trusted and valued partner of the client CIO/CTO and team.
- Maintaining strong expertise and knowledge of current and emerging technologies and products.
- Code! We don’t subscribe to the “post-technical” ivory tower leadership style.
- Assess current state of an organization
Here’s what we’re looking for:
- You are equally happy coding and leading a team to implement a solution
- You have a track record of innovation and expertise in Data Engineering
- You’re passionate about craftsmanship and have applied your expertise across a range of industries and organizations
- You have a deep understanding of data modeling and experience with data engineering tools and platforms such as Kafka, Spark, and Hadoop
- You have built large-scale data pipelines and data-centric applications using Big Data tooling like Hadoop, Spark, Hive, Oozie, and Airflow in a production setting.
- You’ve tackled challenges of persisting, working with, and exposing metadata from data engineering processes using tools such as Apache Atlas, Cloudera Navigator, etc.
- Hands-on experience building Data Engineering tooling with the Microsoft Azure Data Engineering and Analytics stacks including ADLS, Azure Synapse Analytics, Polybase, ADF, Azure Event Hub, Azure Databricks, Active Directory, and PowerBI.
- Hands-on experience with event streaming with modern event streaming tooling like Pulsar, Kafka, Kinesis. Understanding of when streaming vs. batch processing is appropriate, and tradeoffs in a given context
- Hands-on experience with MPP query engines like Presto, Dremio, and Spark SQL.
- You are comfortable applying data security strategy to solve business problems
- You are able to contrast the use of managed services vs custom built ones