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Senior Data Engineer

Flex is building a finance super app for business owners — reimagining every single aspect of the financial workflow and financial services for any entrepreneur. The company has grown revenue 25x+ since publicly launching in September 2023 and is on track to achieve profitability by early 2025. Flex is focused on mid-market businesses ($3 - $100M revenue) that are largely overlooked by existing fintech solutions and reliant on slow and outdated regional banks.  We are targeting a ~$1T revenue opportunity that is largely up for grabs.


Flex is a fully remote company and this role can be performed from anywhere.


The Role


We are looking for engineers who are excited to be part of our early story and help us build a diverse and vibrant company. As a senior data engineer you will be responsible for building systems that bridge the gap between raw business data and consumable data products that the business can trust and take action on. You should have a strong sense of ownership and enjoy taking projects from inception to release. As an early employee, you’ll be working with a nimble team of committed and talented engineers and having a large, long-term impact on technical design and engineering culture.


What You’ll Do
  • Collaborate with stakeholders across the company to build aggregated and curated datasets, dashboards, and APIs to support getting the right data to the right people at the right time.
  • Architect, implement, and manage batch and real-time data pipelines, models, and ETLs to surface new internal and third-party data sources for easy analysis.
  • Identify gaps and invent processes, automated scripts, and tools to efficiently carry out data processing tasks in a scalable fashion.
  • Utilize logging, observability, and notifications for workflows.
  • Contribute to advancing goals around data governance policy creation/enforcement, business metadata cataloging, and access control.
  • Own the process and automation for data intake, QA, and data delivery.
  • Be a catalyst for driving best-in-class technology frameworks and tooling while staying engaged with the latest technology trends.


What You Need
  • Advanced experience building, optimizing, and maintaining data pipelines and data sets.
  • Demonstrated strong experience working with relational databases, query authoring as well as working familiarity with a variety of databases and data warehouses like Postgres, Snowflake, or similar.
  • Ability to perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
  • Strong analytic skills related to working with unstructured datasets.
  • Experience with data pipeline and workflow management tools like Airflow.
  • Familiarity with cloud based providers like Google Cloud, AWS, or Azure and related data services like BigQuery, Dataproc, Dataflow, etc.
  • Experience with programming languages like Python, C#, Java, Scala, etc.
  • Knowledge of Retool or Tableau.
  • Exposure to stream-processing systems: Beam, Spark Streaming, Kafka Streams, etc.
  • Four or more years of relevant industry experience with a track record of shipping high-quality products and features at scale.


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Average salary estimate

$140000 / YEARLY (est.)
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$120000K
$160000K

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What You Should Know About Senior Data Engineer, Flex

Are you ready to take your data engineering skills to the next level? At Flex, a rapidly growing finance super app company, we are on the lookout for a Senior Data Engineer to join our dynamic remote team. Flex is dedicated to transforming financial workflows for mid-market businesses, offering you the opportunity to make a significant impact on an industry largely overlooked by current fintech solutions. As a Senior Data Engineer at Flex, you will be at the forefront of building systems that connect raw business data with actionable insights. You’ll work collaboratively with stakeholders across the organization to create aggregated datasets, dashboards, and APIs that ensure decision-makers have the right data at their fingertips. Your responsibilities will include architecting and managing both batch and real-time data pipelines while identifying automation opportunities that streamline data processes. You’ll also play a vital role in establishing and enforcing data governance policies, giving you a chance to contribute to the company culture and technical design from the ground up. If you thrive in an environment where autonomy and ownership are celebrated, and where your work directly influences the direction of a fast-growing company, Flex could be the perfect fit for you. With competitive compensation and a focus on innovation, you will have the chance to grow alongside a team of talented engineers dedicated to excellence. Don’t miss out on this chance to be part of something big!

Frequently Asked Questions (FAQs) for Senior Data Engineer Role at Flex
What are the responsibilities of a Senior Data Engineer at Flex?

As a Senior Data Engineer at Flex, your responsibilities include collaborating with stakeholders to build curated datasets, designing and managing data pipelines, identifying process gaps, and enhancing data governance policies. You will ensure the delivery of high-quality data products that the business can rely on, making a significant impact in how our teams access and utilize data.

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What qualifications are required for a Senior Data Engineer at Flex?

To qualify for the Senior Data Engineer position at Flex, candidates should have at least four years of relevant experience in data engineering, advanced skills in building and maintaining data pipelines, and proficiency with databases like Postgres and Snowflake. Familiarity with data management tools and cloud services such as AWS or Google Cloud is also necessary, along with programming experience in languages like Python or Java.

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How does the Senior Data Engineer contribute to Flex's growth?

The Senior Data Engineer at Flex plays a crucial role in promoting data-driven decision-making throughout the organization. By architecting efficient data pipelines and creating reliable data products, you will help propel the company towards achieving its ambitious growth milestones. Your work will directly influence Flex’s ability to innovate and serve its target market effectively.

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What tools and technologies will a Senior Data Engineer at Flex work with?

A Senior Data Engineer at Flex will engage with a variety of tools and technologies including Airflow for workflow management, Relational databases such as Postgres, and data processing services in cloud environments like Google Cloud and AWS. Experience with ETL frameworks, data visualization tools like Retool or Tableau, and stream-processing systems like Spark Streaming or Kafka Streams is also beneficial.

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What is the work culture like for a Senior Data Engineer at Flex?

Flex offers a fully remote work environment that emphasizes innovation, collaboration, and ownership. As a Senior Data Engineer, you will join a motivated team where your contributions can shape the technical landscape of the company. The culture at Flex supports growth, creativity, and continuous learning, making it an exciting place for engineering professionals.

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Common Interview Questions for Senior Data Engineer
Can you describe your experience with building and maintaining data pipelines?

When discussing your experience with data pipelines, focus on specific projects where you successfully architected or optimized pipelines. Highlight any tools or languages you used, such as Airflow or Python, and details about the data sources, the volume of data managed, and how your work benefited the company.

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How do you ensure data quality in your projects?

To ensure data quality, explain your approach to data validation and testing. Mention any processes you implemented for QA, such as automated testing frameworks, and how you check for data integrity or completeness before delivery to stakeholders.

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How would you approach collaborating with non-technical stakeholders?

Describe your communication style and strategy for making technical concepts accessible. Emphasize your experience gathering requirements through meetings and feedback sessions, ensuring that the data solutions you provide meet business needs.

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What strategies do you use for troubleshooting data-related issues?

Outline your methodical approach to root cause analysis when faced with data issues. Discuss specific tools you use for logging and monitoring, and provide an example of a challenging troubleshooting scenario and how you resolved it.

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Describe your experience with cloud technology in data engineering.

Discuss the cloud platforms you have worked with, such as AWS or Google Cloud. Explain how you utilize their specific data services like BigQuery for analytics or Lambda for data processing, and mention any projects where cloud technology significantly improved your work.

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What types of datasets are you familiar with, especially unstructured data?

Talk about your experience handling both structured and unstructured datasets. Provide examples of the types of unstructured data you've worked with and how you've extracted actionable insights from them using tools or programming techniques.

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How do you stay updated with the latest trends in data engineering?

Share your commitment to continuous learning through various methods such as following industry blogs, participating in webinars, and attending conferences. Mention any relevant certifications or courses you’ve completed and how they’ve enhanced your skills.

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Can you explain the ETL process you typically follow?

Detail the ETL (Extract, Transform, Load) process you've implemented in previous projects. Highlight how you extract data from various sources, transform it using data wrangling techniques, and load it into data warehouses or databases for consumption.

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Describe a challenging project you worked on as a data engineer.

Provide a narrative of a challenging but successful data engineering project. Focus on the problems you encountered, your approach to solving them, and the positive results achieved for the team or company.

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What role does data governance play in your work?

Discuss your understanding of data governance principles and how they impact data engineering projects. Provide examples of how you contribute to data governance, such as data stewardship and implementing policies for access control.

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Full-time, remote
DATE POSTED
January 10, 2025

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