Data Engineer with SQL and Python expertise
Core
Design, build, and maintain scalable ETL/ELT pipelines and data workflows for finance, trading, and enterprise clients using Python and SQL.
Role type
Senior Data Engineer (Cloud/Infrastructure)
Builds
Production-grade data pipelines, batch and near-real-time data workflows, and cloud-native data architectures.
Domain
Finance, Trading, Enterprise Technology, Cloud Infrastructure
Required skills
Python, SQL, Cloud Infrastructure (Azure), CI/CD, Infrastructure-as-Code, Data Orchestration (Airflow, dbt), Containerization (Docker, Kubernetes), Data Pipeline Development, Legacy System Migration, Performance Optimization, Data Quality & Observability, Technical Mentorship
Preferred skills
Experience in finance/trading/regulated settings, Databricks, Full data lifecycle management
Technologies
Airflow, Azure, CI/CD, Databricks, Docker, Kubernetes, dbt, Python, SQL
Responsibilities
Develop scalable ETL/ELT pipelines utilizing Python and SQL; Design and manage batch and near-real-time data workflows; Integrate various data sources from Azure Blob, ADLS, alongside relational and non-relational systems; Transition legacy data architectures to modern cloud-native environments; Optimize workloads to enhance performance, minimize costs, and ensure fault tolerance; Maintain data quality, observability, and reliability across pipelines; Take ownership of critical infrastructure components for batch and streaming systems; Mentor junior engineers through code reviews and architectural guidance; Automate and standardize pipelines to reduce overhead and boost velocity; Contribute to internal tools, documentation, and engineering best practices; Collaborate directly with client engineering teams across finance, trading, and enterprise technology; Engage in greenfield builds, system migrations, and enterprise-scale data transformations; Collaborate as a true partner in shaping data product strategies.
