Senior Data Engineer
1 week ago
Engineering - Software (Information & Communication Technology)
Full time
Add expected salary to your profile for insights
About the client:
Our client is one of the world's second-largest investment firm with 30 million investors changing the way the world invests and offering a wide range of investment options through one, easy-to-use app.
Position Overview:
About the client:
Our client is one of the world's second-largest investment firm with 30 million investors changing the way the world invests and offering a wide range of investment options through one, easy-to-use app.
Position Overview:
We are looking for a Senior Data Engineer who has previous experience leading implementations and roll-out of a data lakehouse, preferably in regulated environments. Experience as a leader is essential and this role will likely progress to Engineering Manager as opposed to Tech Lead within 12 to 24 months, all being well.
This person will:
- Work with our Engineers and Tech Lead to design, build, and roll out a metadata-driven, incrementally loading data lakehouse solution on AWS.
- Support Data Quality and Data Governance processes by writing maintainable, well-documented, and resilient code.
- Support existing infrastructure and processes working closely with the wider Data & Analytics team to ensure accessible and timely data.
- Monitor, test, and report on the current data lake processes and work with the Product Owner to appropriately prioritise correction or migration to the new lakehouse.
- Contribute to the learning and development of our existing crew, providing knowledge share sessions to ensure we're all along for the ride.
- Support the leadership and management of the Data Engineering team.
- Strong experience working in Cloud-based Engineering teams, preferably using AWS.
- Experience leading teams, prioritising effort, and focussing effort strategically and tactically.
- Solid understanding of dimensional modelling, with Data Vault experience a bonus.
- Thorough understanding of Python and SQL for data exploration and transformation, ideally within Spark environments (Pyspark, SparkSQL) such as within Glue jobs.
- Strong written and oral communication skills and presentation skills with the ability to translate business needs to system and software/data requirements.
- Strong analysis and analytical skills with attention to detail within complex systems and datasets, particularly on relationships between them.
- Solid understanding of version control systems, specifically Git.
- Experience working in Data & Analytics teams with Data Engineers, Analysts, Scientists on on-premises or cloud-based environments.
- Experience with or knowledge of working with SaaS products, CRM and ERP systems, and generally working with data in different formats, such as flat files, APIs, JSON, and RDBMS.
- Good understanding of lean and Agile principles, including Shift left, DevOps, CloudOps, DataOps, CI/CD & with a SRE mindset.
- Experience working in complex Data environments, including with ETL processes/data integration frameworks, such as with Data Lakehouses, Data Warehouses and Data Lakes.
- A self-starter who's comfortable with ambiguity and demonstrable learning agility.
- Experience with Data Visualization tools (Tableau is preferred) or business teams who used visualisation tools.
- Knowledge of the financial services industry, particularly Investment Management.
- Experience in setting up, operating, and monitoring a technical platform and its associated technologies.
- Capability to question the status quo, challenge yourself and the business on the value that will be delivered to our customers with clear justification for change.
- Lead issue resolution, identifying root cause and implementing solutions.
- Experience designing and building metadata-driven, incremental-load type warehouses on AWS.
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