Verified Job
IT / Software / Data Analyst
Senior Python Engineer
IT / Software / Data Analyst
#706254
Remote / WFH
Job Description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Lifelink Healthtech LLC, is seeking the following. Apply via Dice today!
Only Local to Chicago IL
Required Skills
• Python expertise with deep experience in pandas for ETL/ELT and data wrangling (vectorization, memory management, IO, time series).
• Hands-on experience with Snowflake (SQL, performance tuning, warehouse configuration).
• Hands-on experience with Snowpark (Python) for scalable transformations.
• Strong FastAPI experience building production services (dependency injection, Pydantic models, async IO).
• Practical knowledge of Kafka (consumer groups, offsets, partitions, schema management).
• Experience designing event-driven microservices.
• Proficiency with Docker and Kubernetes (deployment strategies, networking, volumes; service meshes a plus).
• Solid understanding of testing, code quality, design patterns, API design, and clean architecture.
• Experience with CI/CD (GitHub Actions, GitLab CI, or Azure DevOps).
• Experience with IaC (Terraform or Helm preferred).
• Familiarity with data modeling and SQL.
• Familiarity with GitHub Copilot or similar AI-assisted coding tools.
Nice to Have (Optional)
• Financial Services industry exposure.
We are seeking a Python Developer with strong expertise in data transformation, pandas, and modern data engineering practices. The ideal candidate will design and implement scalable data pipelines and APIs, leveraging Snowflake, Snowpark, and containerized environments. Experience with FastAPI and Kubernetes is essential. Familiarity with the financial services industry is a plus.
Project Overview/Role
• Design & Build Data Pipelines: Create reliable, testable data transformation workflows using Python (pandas, PySpark/Snowpark), optimizing for performance and maintainability.
• Snowflake Engineering: Implement Snowflake objects (tables, stages, tasks), write efficient SQL, develop Snowpark-based transformations; manage performance (clustering, warehouses, caching) and cost.
• Service Development (FastAPI): Build RESTful/JSON APIs and backend services in FastAPI to expose data and business logic; implement authentication/authorization, rate limiting, and request validation.
• Containerization & Orchestration: Package services with Docker and deploy/operate them on Kubernetes; manage manifests, Helm charts, ConfigMaps/Secrets, health probes, autoscaling, and observability.
• Event-Driven Architecture: Produce/consume Kafka topics; design schemas (Avro/JSON/Protobuf), ensure idempotency, implement exactly-once/at-least-once semantics where appropriate; apply stream processing patterns.
• Quality & Reliability: Write unit/integration tests, data validation checks, and contract tests; implement CI/CD (linting, type checks, security scans, test automation) and support blue/green or canary releases.
• Observability & Operations: Instrument services with logging, metrics, and tracing (e.g., OpenTelemetry); build dashboards and alerts.
• Collaboration: Partner with product, analytics, and platform teams; document designs, APIs, SLAs, and runbooks; participate in reviews and sprint ceremonies.
Only Local to Chicago IL
Required Skills
• Python expertise with deep experience in pandas for ETL/ELT and data wrangling (vectorization, memory management, IO, time series).
• Hands-on experience with Snowflake (SQL, performance tuning, warehouse configuration).
• Hands-on experience with Snowpark (Python) for scalable transformations.
• Strong FastAPI experience building production services (dependency injection, Pydantic models, async IO).
• Practical knowledge of Kafka (consumer groups, offsets, partitions, schema management).
• Experience designing event-driven microservices.
• Proficiency with Docker and Kubernetes (deployment strategies, networking, volumes; service meshes a plus).
• Solid understanding of testing, code quality, design patterns, API design, and clean architecture.
• Experience with CI/CD (GitHub Actions, GitLab CI, or Azure DevOps).
• Experience with IaC (Terraform or Helm preferred).
• Familiarity with data modeling and SQL.
• Familiarity with GitHub Copilot or similar AI-assisted coding tools.
Nice to Have (Optional)
• Financial Services industry exposure.
We are seeking a Python Developer with strong expertise in data transformation, pandas, and modern data engineering practices. The ideal candidate will design and implement scalable data pipelines and APIs, leveraging Snowflake, Snowpark, and containerized environments. Experience with FastAPI and Kubernetes is essential. Familiarity with the financial services industry is a plus.
Project Overview/Role
• Design & Build Data Pipelines: Create reliable, testable data transformation workflows using Python (pandas, PySpark/Snowpark), optimizing for performance and maintainability.
• Snowflake Engineering: Implement Snowflake objects (tables, stages, tasks), write efficient SQL, develop Snowpark-based transformations; manage performance (clustering, warehouses, caching) and cost.
• Service Development (FastAPI): Build RESTful/JSON APIs and backend services in FastAPI to expose data and business logic; implement authentication/authorization, rate limiting, and request validation.
• Containerization & Orchestration: Package services with Docker and deploy/operate them on Kubernetes; manage manifests, Helm charts, ConfigMaps/Secrets, health probes, autoscaling, and observability.
• Event-Driven Architecture: Produce/consume Kafka topics; design schemas (Avro/JSON/Protobuf), ensure idempotency, implement exactly-once/at-least-once semantics where appropriate; apply stream processing patterns.
• Quality & Reliability: Write unit/integration tests, data validation checks, and contract tests; implement CI/CD (linting, type checks, security scans, test automation) and support blue/green or canary releases.
• Observability & Operations: Instrument services with logging, metrics, and tracing (e.g., OpenTelemetry); build dashboards and alerts.
• Collaboration: Partner with product, analytics, and platform teams; document designs, APIs, SLAs, and runbooks; participate in reviews and sprint ceremonies.
