Senior Data Engineer

• Architect, implement, and operate the complete data infrastructure pipeline for research and trading operations
• Design, build, and optimize scalable pipelines for ingesting, transforming, and integrating market data, news feeds, and unstructured data
• Ensure data quality, consistency, and real-time monitoring using dbt and data validation libraries
• Develop processes to normalize and organize the data warehouse for use across departments
• Apply data management practices to ensure scalable, available, and efficient data storage
• Maintain data integrity, security, and performance at scale for trading and research infrastructure
• Collaborate with research and analytics teams to understand data needs and build frameworks for exploration, analysis, and model development
• Create tools for overlaying data from multiple sources
• Optimize hardware and software resources to balance performance with cost control
• Evaluate and adopt suitable technologies and align systems with data management best practices

• Strong problem-solving and analytical thinking
• Clear communication skills for cross-functional collaboration
• Proficiency in building robust data quality checks for ingested data
• Experience identifying anomalies in ingested data
• Strong proficiency in writing complex SQL queries and optimizing performance
• Proficiency in Python or Java/Scala
• Experience building and maintaining complex ETL pipelines with Apache Airflow, dbt, or custom scripts
• Strong understanding of dimensional modeling, star/snowflake schemas, and normalization/denormalization principles
• Proven experience with Snowflake, Redshift, BigQuery, Synapse, or similar platforms
• Expert knowledge of Apache Spark, Kafka, Flink, or similar
• Strong understanding of data security and privacy standards
• Degree in Computer Science, Engineering, Mathematics, or a related field is preferred
• Familiarity with AWS, GCP, or Azure and their data services, proven by relevant certifications is preferred
• Experience with data quality frameworks such as Great Expectations or Deequ is preferred
• Experience with Git/GitHub or similar for code versioning is preferred
• Experience with infrastructure-as-code tools such as Terraform or CloudFormation is preferred
• Exposure to Docker and Kubernetes is preferred
• Familiarity with data governance, data lineage, and catalog tools is preferred
• Hands-on experience with observability and monitoring tools for data pipelines is preferred
• Knowledge of machine learning pipelines is preferred
• Prior experience in a trading or financial services environment is preferred