Senior Data Engineer (Python)
Software Development
WFA Digital Insight
As the demand for skilled data engineers continues to skyrocket, with a growth rate of 25% in 2025, professionals with expertise in Python and data infrastructure are in high demand. Proxify, a platform connecting top developers with exciting opportunities, is now looking for a Senior Data Engineer to lead the charge in architecting and scaling data foundations for high-growth client products. With a strong focus on remote work and digital skills, this role offers a unique chance for growth-oriented professionals to make a significant impact. Before applying, candidates should be aware that this position requires a deep understanding of data engineering principles, a passion for innovation, and excellent collaboration skills.
Job Description
About the Role
The Senior Data Engineer role at Proxify is a critical position that involves designing, building, and maintaining large-scale data pipelines to support the growth of client products. This role is perfect for a skilled data engineer who is passionate about working with Python and has a deep understanding of data infrastructure. As a Senior Data Engineer, you will be responsible for ensuring the reliability, efficiency, and scalability of data pipelines, collaborating with cross-functional teams to drive business growth. The ideal candidate will have a strong background in building complex data processing applications using Python, with expertise in tools such as Pandas, PySpark, or Dask. You will also have advanced SQL skills, including experience with complex transformations, window functions, and query optimization in cloud warehouses. Proxify values innovation, collaboration, and growth, and this role is an excellent opportunity for a talented data engineer to join a dynamic team and contribute to the company's mission. Proxify is committed to providing a supportive and inclusive work environment, with a strong focus on remote work and digital skills. As a remote worker, you will have the flexibility to work from anywhere, with a high degree of autonomy and a collaborative team to support you.What You Will Do
- Design, build, and maintain large-scale data pipelines to support client product growth
- Collaborate with cross-functional teams to identify and prioritize data engineering projects
- Develop and implement data models, including Dimensional Modeling and Data Vault 2.0
- Implement rigorous automated testing and monitoring to ensure data integrity and reliability
- Optimize warehouse storage and compute costs while reducing pipeline latency
- Partner with Data Scientists and Product Managers to translate business requirements into technical data models
- Promote a "DataOps" culture within the team, conducting code reviews and sharing best practices
- Work with Apache Airflow, Prefect, or Dagster to manage complex dependency graphs
- Ensure data security and compliance with relevant regulations
What We Are Looking For
- 5+ years of experience building complex data processing applications using Python
- Advanced SQL skills for complex transformations, window functions, and query optimization
- Deep experience with dbt (data build tool) for managing the T in ELT, including documentation and testing
- Proven experience with Apache Airflow, Prefect, or Dagster for managing complex dependency graphs
- Hands-on experience with Snowflake, BigQuery, or AWS Redshift
- Strong understanding of Dimensional Modeling (Star/Snowflake schema) and Data Vault 2.0
- Experience with Git, Docker, and implementing CI/CD for data pipelines
- Excellent collaboration and communication skills
Nice to Have
- Experience building Real-time Pipelines using Kafka or Flink
- Familiarity with Data Contracts and Data Quality frameworks (Great Expectations, Monte Carlo)
- Knowledge of Vector Databases (Pinecone, Milvus) for AI/LLM applications
- Infrastructure as Code (Terraform) experience
Benefits and Perks
- Enjoy on-time monthly payments with flexible withdrawal options
- Predictable project hours with consistent 8-hour working days
- Up to 24 flex days off per year without losing pay
- Career-accelerating positions at cutting-edge companies
- Hand-picked opportunities, personally matched to your skills and interests
- One seamless process, multiple opportunities with no extra assessments
- Opportunity to work with a talented team of professionals in a dynamic and supportive environment
- Access to cutting-edge tools and technologies to help you grow and develop as a professional
- Flexible and remote work arrangement to support your work-life balance
- Professional development opportunities to help you achieve your career goals
- A collaborative and inclusive work environment that values diversity and promotes equal opportunities
How to Stand Out
- To stand out as a candidate, make sure to highlight your experience with Python and data infrastructure, and be prepared to provide examples of your work.
- When applying, include a portfolio or GitHub repository that showcases your data engineering projects and skills.
- Be prepared to discuss your experience with data modeling, including Dimensional Modeling and Data Vault 2.0, and how you have applied these concepts in previous roles.
- Pay attention to the company culture and values, and be prepared to discuss how you can contribute to a remote and dynamic team.
- Don't be afraid to ask questions about the company, the role, and the team during the interview process.
- Make sure to research the company and the role thoroughly, and be prepared to discuss your skills and experience in relation to the job requirements.
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