Data Engineer
Posted
Summary
Data Engineer at Marshall Wace, a global hedge fund, joining a data team that builds and maintains thousands of data ingestion pipelines and the platforms that run and monitor them, feeding investment decisions. Day-to-day involves Python/C#/Scala/Java/Go coding with SQL, Snowflake, Docker/Kubernetes and ETL tools like Airflow, Spark and Kafka.
Role Overview:
We are looking for an ambitious, enthusiastic and highly motivated Data Engineer to join our Data team that spans across our international offices. Data engineers work closely with almost every team in the firm: investment, business and technical. The team builds and maintains thousands of data ingestion processes of varying complexity, feeding investment decisions and facilitating critical operations. The data team also develops and owns the platforms that run and monitor these processes, tools and libraries within them, and
complex systems that model the firm's view of the financial world. The role is fast moving and varied, and will suit someone that enjoys direct business interaction, is delivery focused and works well under pressure. Responsibilities: Building easily supportable data ingestion pipelines, platforms and systems. Digging into and exploring data identifying features and issues and communicating them toothers clearly and concisely. Standardisation and development of ingestion methodologies, including promoting those standards to other teams across the firm in the form of tools and libraries Ensuring that systems are highly effective for downstream teams, as well as reliable, scalable and flexible over the long term as business needs grow and change. Supporting, monitoring and improving existing systems and ingestion pipelines. Requirements: Broad technical knowledge, particularly with respect to the processing and exploration of data and an affinity for learning about new technologies. A passion for automation and continual improvement, with a track record of identifying high value automation opportunities. Ability to identify patterns and establish standards that reduce development time and increase reliability. Ability to build positive and collaborative relationships with colleagues across teams and geographies. Systematic and methodical approach to problem-solving and debugging. Technologies: The ideal candidate will have: Experience with coding in Python / C# / Scala / Java / Go or equivalent. Experience working with a variety of data storage and manipulation tools such as SQL, Pandas, Elasticsearch & Kibana, Snowflake. Experience with containerisation and orchestration technologies like Docker / Kubernetes / Helm / Flux. Experience with various ETL/ELT technologies such as Airflow /Argo / Dagster / Spark / Hive. Additional beneficial skills or experience: Familiarity with data visualisation tools. Experience with Apache Kafka or similar stream processing platforms and concepts. Cross asset financial markets experience - Equities, FX, Options, Futures, Fixed Income.
complex systems that model the firm's view of the financial world. The role is fast moving and varied, and will suit someone that enjoys direct business interaction, is delivery focused and works well under pressure. Responsibilities: Building easily supportable data ingestion pipelines, platforms and systems. Digging into and exploring data identifying features and issues and communicating them toothers clearly and concisely. Standardisation and development of ingestion methodologies, including promoting those standards to other teams across the firm in the form of tools and libraries Ensuring that systems are highly effective for downstream teams, as well as reliable, scalable and flexible over the long term as business needs grow and change. Supporting, monitoring and improving existing systems and ingestion pipelines. Requirements: Broad technical knowledge, particularly with respect to the processing and exploration of data and an affinity for learning about new technologies. A passion for automation and continual improvement, with a track record of identifying high value automation opportunities. Ability to identify patterns and establish standards that reduce development time and increase reliability. Ability to build positive and collaborative relationships with colleagues across teams and geographies. Systematic and methodical approach to problem-solving and debugging. Technologies: The ideal candidate will have: Experience with coding in Python / C# / Scala / Java / Go or equivalent. Experience working with a variety of data storage and manipulation tools such as SQL, Pandas, Elasticsearch & Kibana, Snowflake. Experience with containerisation and orchestration technologies like Docker / Kubernetes / Helm / Flux. Experience with various ETL/ELT technologies such as Airflow /Argo / Dagster / Spark / Hive. Additional beneficial skills or experience: Familiarity with data visualisation tools. Experience with Apache Kafka or similar stream processing platforms and concepts. Cross asset financial markets experience - Equities, FX, Options, Futures, Fixed Income.