Lead Data Engineer
Elasticsearch (regular) CD (regular) CI (regular) DevOps (regular) Cloud (regular) ETL tools (regular) Scala (regular) Java (regular) SQL (advanced) Python (advanced) For our client (software house), we are currently looking for an experienced engineer for the position of Lead Data Engineer. The projects are banking and broadly defined financial industry. Our client is building a revolutionary data analytics ecosystem to generate business insights and provide great customer experience from well-managed and trusted data assets. As a key member of the technical team alongside Engineers, Data Scientists and Data Users, you will be expected to define and contribute at a high-level to many aspects of our collaborative Agile development process. *we are open to your financial expectations Responsibilities: Owning and delivering the automation of data engineering pipelines through the removal of manual stages Developing comprehensive knowledge of the bank’s data structures and metrics, advocating change where needed for product development Leading and delivering data engineering strategies to build a scalable data architecture and customer feature rich dataset for data scientists Leading and developing solutions for streaming data ingestion and transformations in line with streaming strategy Educating and embedding new data techniques into the business through role modelling, training and experiment design oversight Work closely with all teams (including virtual teams based in non UK locations), creating a strong culture of transparency and collaboration Leading the engineering team to set the standards of best practice and mentor throughout the deliveries. Requirements: 2+ years in team leading role Professional software development experience within data environment/s Programming experience in Java, Scala, and Spark Proficient in SQL and relational database design Knowledge of big data platforms such as Snowflake, AWS Redshift, Postgres, MongoDB, Neo4J and Hadoop Good knowledge of cloud technologies such as Amazon Web Services, Google Cloud Platform and Microsoft Azure Experience of ETL technical design, automated data quality testing, QA and documentation, data warehousing, data modelling and data wrangling
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