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Senior Staff Data Engineer

We’re changing the way people connect to social care. 


At Findhelp, we’ve built a comprehensive platform of products and services that make it easy for you to connect people to resources, follow them on their journey, and track your impact in a fast and reliable way. Our industry-leading social care network includes more than half a million local, state, and national programs that serve every ZIP Code in the country, from rural areas to major metropolitan centers. 

Findhelp is headquartered in Austin, Texas and has been enabling healthcare, government, education, and other organizations to connect people with the social care resources that serve them, with privacy and security, since 2010.


As a mission driven organization, we are focused on creating a positive impact by connecting people in need to the programs that serve them with dignity and ease. Powered by our proprietary technology that enables people to find the resources available in their area, we have helped millions of Seekers find food, health, housing and employment programs.


We are seeking a skilled Staff Data Engineer to own and enhance our data integration processes, with a focus on uploading and syncing data related to 211 relationships and other organizational data. This role is critical in ensuring data consistency, automation, and scalability across our data ecosystem. As a Senior Staff Data Engineer, you will be responsible for designing, building, and maintaining data pipelines that transform, load, and synchronize data from various sources into our environment. You will leverage cloud-based batch data load strategies and update APIs to ensure seamless integration. You will also play a key role in optimizing production systems, resolving incidents, and identifying automation opportunities to improve efficiency.


Responsibilities:
  • Data Integration & Processing: Own all data uploading and syncing related to 211 relationships and potentially other organizational datasets.
  • Pipeline Development: Design, build, and maintain scalable data pipelines that transform raw source outputs (e.g., customer 211s) into a structured format for internal use.
  • API-Driven Data Uploads: Partner with Programs Team on creation and updating APIs to upload and synchronize bulk data efficiently.
  • Database Design & Documentation: Create and maintain data models, metadata, ETL specifications, and process flows to support business data projects.
  • Production System Monitoring: Monitor, maintain, and optimize data pipelines to ensure reliability, performance, and data integrity.
  • Incident Resolution: Investigate and resolve user-reported incidents related to data syncing, transformation, and pipeline failures.
  • Automation & Optimization: Identify opportunities to automate, consolidate, and simplify data solutions for better scalability.
  • Code Reviews & Best Practices: Conduct periodic code reviews to enforce best practices in design, performance tuning, and maintainability.


Qualifications:
  • 7+ years of experience in data engineering, with a focus on data pipeline development, transformation, and bulk syncing, with experience in one or more languages commonly used for data operations including SQL and Python.
  • Deep knowledge and hands-on experience building/operating highly available, distributed systems of data extraction, ingestion, and processing in cloud environments such as GCP (ideal), Microsoft Azure or AWS.
  • Experience with bulk API integration and JSON processing, including designing, optimizing, and troubleshooting high-volume data exchanges.
  • Demonstrated strength in data modeling, ETL development, and data warehousing.
  • Experience with relational databases such as MySQL (ideal), Oracle, or PostgreSQL.
  • Experience with BigQuery (ideal), Redshift, or Snowflake.
  • Experience in Airflow, GitHub, and CI/CD processes are a must.
  • Ability to troubleshoot and optimize data solutions for performance and reliability.


$142,400 - $213,600 a year
The compensation for this position will be based on a candidate’s job-related skills, experience, education or training, and location.

We value being together 

We believe being together enables stronger relationships, collaboration, and culture.

This position is in office and candidates must be located in Austin, Texas, Madison, Wisconsin, or Denver, Colorado


Perks at Findhelp 

•401k & stock options 

•Free food and onsite gym at our Austin HQ 

•Paid parental leave

•Competitive PTO & 10 paid holidays

•Health, dental, and vision insurance

•Dog-friendly office in Austin HQ

•24/7 access to telemedicine and counseling

•Book Purchasing Program


We’re building a diverse, inclusive team


You’re welcome here. We want everyone to be able to easily connect to the help they need, and we want our teams to reflect and represent our communities. It is our policy to recruit, hire, train, and promote individuals, as well as administer any and all Company policies, without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin or ancestry, physical and mental ability, political affiliation, race, religion, creed, sexual orientation, socio-economic status, veteran status, or any other protected class, in accordance with applicable laws. Accommodations are available for applicants with disabilities.


Here are some of the ways we support our staff:

•Culture Committee 

•Leadership Development Training

•Paid Volunteering Time



Average salary estimate

$178000 / YEARLY (est.)
min
max
$142400K
$213600K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Staff Data Engineer, Findhelp, A Public Benefit Corporation

At Findhelp, we’re reshaping the social care landscape, making it easier for people to connect with the resources they need. We’re on the lookout for a Senior Staff Data Engineer to join our Austin team and satisfy our ambition for creating impactful data solutions. In this role, you’ll be the backbone of our data integration processes, focusing primarily on data synchronization related to 211 relationships and other critical datasets. Every day, you'll design, build, and maintain scalable data pipelines that not only transform and load data, but also ensure that our ecosystem remains consistent and reliable. With over half a million programs accessible through our platform, the quality of our data directly affects our mission. You will utilize innovative cloud-based solutions for efficient data handling, and partner with our Programs Team to develop APIs that facilitate seamless uploads and data synchronization. Monitoring and optimizing our production systems will be key, making sure that all data flows as smoothly as possible. You'll also be influential in identifying automation opportunities, helping us to improve efficiency and scalability. If you have at least seven years of experience in data engineering, a solid understanding of cloud environments, and a passion for creating data-driven solutions that truly make a difference in people’s lives, we'd love for you to be a part of our mission at Findhelp.

Frequently Asked Questions (FAQs) for Senior Staff Data Engineer Role at Findhelp, A Public Benefit Corporation
What are the responsibilities of a Senior Staff Data Engineer at Findhelp?

As a Senior Staff Data Engineer at Findhelp, your primary responsibilities will include owning all data upload and synchronization processes related to 211 relationships, designing and maintaining scalable data pipelines, and optimizing production systems. You'll also conduct code reviews, create data models, and collaborate closely with our Programs Team on API developments.

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What qualifications are required for the Senior Staff Data Engineer position at Findhelp?

To be successful as a Senior Staff Data Engineer at Findhelp, candidates should possess at least seven years of experience in data engineering, with a strong focus on data pipeline development and transformation. Proficiency in SQL and Python, as well as hands-on experience with cloud environments like GCP, AWS, or Azure, are essential. Familiarity with relational databases, particularly MySQL, and experience with data processing tools are also required.

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How does Findhelp ensure data integrity for its users?

Findhelp places a strong emphasis on data integrity through constant monitoring and optimization of its production systems. As a Senior Staff Data Engineer, you'll play a crucial role in resolving incidents related to data syncing and transformation processes, ensuring that the data not only meets the quality standards but also enhances user trust and experience.

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What cloud technologies will the Senior Staff Data Engineer work with at Findhelp?

In the role of Senior Staff Data Engineer at Findhelp, you'll work with cloud technologies predominantly on Google Cloud Platform (GCP), though experience with AWS or Azure is also welcomed. You'll utilize cloud-based data load strategies to streamline processes and maintain data integrity across our ecosystem.

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What kind of culture does Findhelp foster for its data engineering team?

Findhelp nurtures a collaborative and inclusive workplace culture, promoting diversity and innovation within the team. As a Senior Staff Data Engineer, you will be part of a mission-driven organization, where your expertise not only impacts data solutions but also contributes to the larger goal of connecting individuals in need with crucial resources.

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Common Interview Questions for Senior Staff Data Engineer
Can you describe your experience with building scalable data pipelines as a Senior Staff Data Engineer?

When answering this question, focus on specific projects where you've designed and implemented data pipelines. Discuss the technologies you used, the challenges you faced, and how you ensured the pipelines were scalable to accommodate increasing data loads.

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What are your methods for ensuring data quality and integrity in your engineering processes?

It's essential to integrate methods for data validation and error handling in your processes. Discuss how you monitor data quality metrics and implement checks at various stages in your data pipeline to ensure reliability.

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How do you handle incident resolution when a data pipeline fails?

Describe a structured approach for tackling data pipeline failures. Include how you investigate the root cause, collaborate with your team for quick resolution, and prevent similar incidents from happening in the future.

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What is your experience with cloud environments like GCP or AWS in data engineering?

Highlight your hands-on experience with specific services within these cloud platforms. Discuss the types of data workloads you've managed and how these environments can enhance data integration and processing.

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How do you perform code reviews to ensure best practices in data engineering?

Explain the criteria you consider during a code review, such as efficiency, readability, and adherence to coding standards. Share how to provide constructive feedback that not only elevates the team's work but also fosters learning.

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Can you explain your experience with ETL and data warehousing solutions?

Discuss specific ETL tools and data warehousing solutions you have utilized, emphasizing their importance in transforming and storing data efficiently for analytics and business intelligence needs.

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How do you approach data modeling for various business projects?

Provide insight into your data modeling process, from gathering requirements to designing the model. Talk about how you collaborate with stakeholders to ensure their needs are met while maintaining best modeling practices.

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What types of APIs have you developed or worked with in relation to data upload processes?

Discuss any specific APIs you have worked with, detailing how they facilitate data synchronization or bulk uploads. Focus particularly on your role in their development or optimization, showcasing your technical skills.

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How do you identify opportunities for automation in data workflows?

Emphasize your proactive approach to identifying repetitive tasks and inefficiencies. Describe the methods or tools you use to automate processes and how these improvements have benefitted your previous projects.

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What strategies do you use to stay updated with the latest trends in data engineering?

Discuss how you prioritize continuous learning in your career. Share resources like blogs, webinars, or communities you engage with, and explain how sharing knowledge within your team helps everyone stay informed.

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