Data Pipeline Development for Fintech Start-up
Budget: $20,000 – $50,000 USD
Data Engineering Role at Fintech Start-up in the NYC Area
This is an opportunity for a short project (roughly 2 months) that has a good chance of growing into a longer term opportunity. We are looking for someone with 3-5 years of experience, who is ideally in the NYC area.
This firm is a start-up led by an experienced executive who has spent their career in senior leadership roles at top hedge funds. In these roles the founder has led quantitative research teams, trading desks, data science teams, quantitative development teams and more traditional s/w development teams. The firm has initial clients lined-up and a pipeline of potential future work.
The primary responsibilities of the role initially are related to data engineering. However, there will be opportunities to take on expanded roles depending on clients’ needs, personal interest and ability to take on more responsibilities:
Data Modeling / Architecture
Building customized and interactive dashboards
Constructing quantitative investment tools
Working directly with clients (e.g., proposals, assessing needs, demos)
Project planning and project leadership
We’re looking for someone who:
Takes a high degree of ownership and pride in their work
Connects with the high-level goals and can work independently
Understands how to deliver quality engineering work
Is curious and interested in learning about new technologies and the investment industry
Wants to to use technology to solve real client problems
Takes initiative and is an independent thinker
Seeks to understand the broader business (e.g., the clients, their problems, the opportunities)
Responsibilities:
Design, develop, and implement robust data pipelines to collect, transform, and store data from various sources.
Build and maintain scalable data warehouses and data lakes to support business intelligence and analytics.
Write and optimize complex SQL queries to extract and analyze data.
Automate data processing tasks to improve efficiency and reduce manual intervention.
Monitor and troubleshoot data pipelines to ensure data integrity and availability.
Collaborate with data scientists and analysts to understand their data requirements and provide solutions.
Document data pipelines and processes for knowledge sharing and future reference.
Experience:
3-5 years of hands-on experience as a Data Engineer or in a similar role.
Proficiency in SQL and experience with relational databases such as MySQL, PostgreSQL, or similar.
Understanding of data warehousing principles and best practices.
Familiarity with data pipeline orchestration tools like Airflow or similar.
Experience working with big data technologies such as Hadoop, Spark, or similar frameworks.
Solid Software Engineering Skills
Familiarity with cloud platforms (AWS, Azure, GCP).
Experience with Databricks is a plus but not required.
Skills:
Strong programming skills in Python.
Excellent problem-solving and analytical skills with a focus on data.
Effective communication and collaboration skills
Empathetic and able to understand client’s and teammates
Ability to work independently and take ownership of projects.
A passion for learning and staying up-to-date with the latest data technologies.
Compensation: Compensation will be competitive and all cash. If things go well, there will be opportunities for equity in the business.
Next steps
Please apply by sending a short cover letter and CV to the address below. We are looking to begin work on these projects in the next 4-6 weeks. That is, the assessment process will not be drawn out.
This is an opportunity for a short project (roughly 2 months) that has a good chance of growing into a longer term opportunity. We are looking for someone with 3-5 years of experience, who is ideally in the NYC area.
This firm is a start-up led by an experienced executive who has spent their career in senior leadership roles at top hedge funds. In these roles the founder has led quantitative research teams, trading desks, data science teams, quantitative development teams and more traditional s/w development teams. The firm has initial clients lined-up and a pipeline of potential future work.
The primary responsibilities of the role initially are related to data engineering. However, there will be opportunities to take on expanded roles depending on clients’ needs, personal interest and ability to take on more responsibilities:
Data Modeling / Architecture
Building customized and interactive dashboards
Constructing quantitative investment tools
Working directly with clients (e.g., proposals, assessing needs, demos)
Project planning and project leadership
We’re looking for someone who:
Takes a high degree of ownership and pride in their work
Connects with the high-level goals and can work independently
Understands how to deliver quality engineering work
Is curious and interested in learning about new technologies and the investment industry
Wants to to use technology to solve real client problems
Takes initiative and is an independent thinker
Seeks to understand the broader business (e.g., the clients, their problems, the opportunities)
Responsibilities:
Design, develop, and implement robust data pipelines to collect, transform, and store data from various sources.
Build and maintain scalable data warehouses and data lakes to support business intelligence and analytics.
Write and optimize complex SQL queries to extract and analyze data.
Automate data processing tasks to improve efficiency and reduce manual intervention.
Monitor and troubleshoot data pipelines to ensure data integrity and availability.
Collaborate with data scientists and analysts to understand their data requirements and provide solutions.
Document data pipelines and processes for knowledge sharing and future reference.
Experience:
3-5 years of hands-on experience as a Data Engineer or in a similar role.
Proficiency in SQL and experience with relational databases such as MySQL, PostgreSQL, or similar.
Understanding of data warehousing principles and best practices.
Familiarity with data pipeline orchestration tools like Airflow or similar.
Experience working with big data technologies such as Hadoop, Spark, or similar frameworks.
Solid Software Engineering Skills
Familiarity with cloud platforms (AWS, Azure, GCP).
Experience with Databricks is a plus but not required.
Skills:
Strong programming skills in Python.
Excellent problem-solving and analytical skills with a focus on data.
Effective communication and collaboration skills
Empathetic and able to understand client’s and teammates
Ability to work independently and take ownership of projects.
A passion for learning and staying up-to-date with the latest data technologies.
Compensation: Compensation will be competitive and all cash. If things go well, there will be opportunities for equity in the business.
Next steps
Please apply by sending a short cover letter and CV to the address below. We are looking to begin work on these projects in the next 4-6 weeks. That is, the assessment process will not be drawn out.