Drweng4d ago

Senior Data Engineer - Data Experience

Singaporesenior

Data EngineerData

0 views0 saves0 applied

Apply Now

Quick Summary

Key Responsibilities

Model, build, and manage data products built atop DRW’s Unified Data Platform.

Technical Tools

Data EngineerData

Requirements

~1 min read

Have extensive experience designing and building data pipelines
Have experience working within modern batch and streaming data ecosystems
An expert in SQL and Java or Python
Extensive knowledge of data modeling techniques
Able to own the delivery of data products, working with analysts and stakeholders to understand requirements and implement solutions
Able to contribute to project management and project reporting
Have experience driving nontrivial data migrations across platforms
Able to establish, follow, and enforce data modeling standards across a large ecosystem.

Responsibilities

~1 min read

→Model, build, and manage data products built atop DRW’s Unified Data Platform.
→Work closely with Data Strategists to determine appropriate data sources and implement processes that onboard and manage new datasets for trading, research, and back-office purposes.
→Design data governance processes that enable discovery, cost-sharing, usage tracking, access controls, and quality control of datasets to address the needs of DRW trading teams and strategies.
→Continually monitor data ingestion pipelines and data quality to ensure stability, reliability, and quality of the data. Design monitoring and quality control software and processes.
→Own the technical aspects of vendor ingestion pipelines, coordinating with vendor relationship managers on upcoming changes, performing routine data operations without breaking internal users, and contributing to the team’s on-call rotation to respond to unanticipated changes.
→Rapidly respond to user requests, identifying platform gaps, and self-service opportunities that make the user experience more efficient.

Responsibilities

~2 min read

→7+ years of experience working with modern data technologies and building data-first products.
→Excellent written and verbal communication skills.
→Proven ability to work in a collaborative, agile, and fast-paced environment, prioritizing multiple tasks and projects, and efficiently handle the demands of a trading environment.
→Proven ability to deliver rapid results within processes that span multiple stakeholders.
→Strong technical problem-solving skills.
→Extensive familiarity with SQL and Java or Python, with a proven ability to develop and deliver maintainable data transformations for production data pipelines.
→Experience leveraging data modeling techniques and ability to articulate the trade-offs of different approaches.
→Experience with one or more data processing technologies (e.g. Flink, Spark, Polars, Dask, etc.).
→Experience with multiple data storage technologies (e.g. S3, RDBMS, NoSQL, Delta/Iceberg, Cassandra, Clickhouse, Kafka, etc.) and knowledge of their associated trade-offs.
→Experience with multiple data formats and serialization systems (e.g. Arrow, Parquet, Protobuf/gRPC, Avro, Thrift, JSON, etc.).
→Experience managing data pipeline orchestration systems (e.g. Kubernetes, Argo Workflows, Airflow, Prefect, Dagster, etc.), delving deeply into low-level details.
→Proven experience in managing the operational aspects of large data pipelines such as backfilling datasets, rerunning batch jobs, monitoring event throughput, and handling dead-letter queues.
→Prior experience triaging data quality control processes, correcting data gaps and inaccuracies.