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Data Engineer

About us

Remo is building the new standard of dementia care. As a virtual dementia care provider, our expert clinical team designs personalized, comprehensive care around patient and family needs (instead of a one-size-fits-all approach). We empower family caregivers by connecting them with a vibrant community of other caregivers, expert content, and tools to manage the entire dementia journey – from anywhere, at any time.

Our mission is simple — to provide accessible, comprehensive, quality dementia care for every person who needs it.

About the role

We are looking for our first highly skilled Data Engineer to play a key role in developing and maintaining our Data and Analytics Platform. As a key member of our team at Remo, you'll be supporting our mission to provide accessible, comprehensive, and quality dementia care by engineering robust data pipelines, developing analytical models, and empowering our stellar team to leverage our data across the organization.

What you’ll be doing

  • Manage the full lifecycle of data at Remo Health, from ingestion to transformation and downstream consumption

  • Design, develop, and maintain data pipelines and ETL processes using ingestion platforms such as Fivetran and tools like Google Cloud Composer (Apache Airflow)

  • Manage the Customer Data Platform and lifecycle

  • Manage GCP services such as BigQuery, Dataflow (Apache Beam), Kubeflow, or Vertex AI Pipelines for data processing and model deployment.

  • Implement and manage tools such as dbt and semantic layer to support data transformations and modeling

  • Optimize SQL queries for data warehousing in BigQuery, including database partitioning strategies

  • Develop Python scripts and/or packages for data processing and automation tasks

  • Act as a lead analyst to empower and support analytical roles across various departments

  • Enable data discovery and provide expert guidance on augmenting and leveraging available data and obtaining missing data

  • Ensure compliance with data governance policies and data loss prevention (DLP) standards

  • Handle Protected Health Information (PHI), Personally Identifiable Information (PII), and de-identified data securely

  • Collaborate with data scientists to codify and deploy machine learning models to staging and production environments

What we’re looking for

  • 3+ years of experience as a Data Engineer and 3+ years of combined experience in a an Analytics Engineering role in the Healthcare industry

  • Experience building, maintaining, and monitoring robust ETL pipelines

  • Someone who has held a lead analytical role in forecasting, cohort analysis, and time-series wrangling using healthcare and product data (required)

  • Experience developing a strategy for a data semantic layer in a healthcare setting (required)

  • Mastery of administering and augmenting BI and other analytical tooling such as Tableau, PowerBI, or similar (required)

  • Hands on (2+ years) Google Cloud Experience: BigQuery, Composer, Dataflow (required)

  • Expert level SQL: Postgres and BigQuery (required)

  • Experience developing and maintaining Python packages used as part of data transformation pipelines (required)

  • Strong experience with transform and modeling tools such as dbt

  • Proficiency in leveraging platforms such as Segment, Fivetran, dbt

  • Experience with version control for data models (Git)

  • Strong understanding of CDC (change data capture);

  • Above all, excellent problem solving, analytical, and communication skills

  • Knowledge of HIPAA/HITRUST compliance and related security best practices

An added BONUS if you have these skills:

  • Hands on experience with Terraform is preferred

  • Having implemented a CDC solution is a huge plus

  • Experience collaborating with Data Science teams to codify and deploy ML models into production a plus

  • Experience enabling the responsible usage of AI within an organization is not required, but highly desirable

  • Experience developing BigQuery datasets, views, and tagging for DLP a huge plus

  • Experience with additional GCP technologies such as Cloud Run / Functions, Scheduler, PubSub a plus

At Remo Health, we value diversity in the workplace because it allows us to better understand and meet the needs of our customers and the communities we serve. We want to ensure every job applicant is treated fairly and with respect regarding race, national or ethnic origin, religion, age, gender, sexual orientation, or disability. If you require any support in the application process, including disability accommodation, please contact hr@remo.health.

We use E-Verify to confirm the identity and employment eligibility of all new hires: Participation Poster (PDF), Right to Work Poster (PDF). Background checks are required for all new hires.

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What You Should Know About Data Engineer, Remo Health

At Remo, we’re on a mission to redefine dementia care, and we need a passionate Data Engineer to join our innovative team! As our first full-time Data Engineer, you will be instrumental in creating and maintaining our Data and Analytics Platform. Imagine crafting data pipelines that not only streamline our operations but also empower caregivers with the insights they need to manage dementia care effectively. You’ll dive deep into data ingestion using advanced tools like Fivetran and orchestrate workflows with Google Cloud Composer. Collaborating closely with our talented team, you’ll ensure that data is not only efficiently gathered but also thoughtfully transformed into actionable insights. A significant aspect of your role will involve optimizing SQL queries and managing our Customer Data Platform, guaranteeing that our analytics processes are smooth and effective. With your expertise in Google Cloud products like BigQuery and Dataflow, you will help us elevate our data capabilities. You’ll also support our analysts in understanding and leveraging data to improve patient care. If you have a strong background in healthcare analytics, a knack for problem-solving, and a passion for making a difference, we’d love to hear from you! Join Remo and be part of a caring, dedicated team that truly values innovation, inclusivity, and community. Together, we can change the landscape of dementia care for the better!

Frequently Asked Questions (FAQs) for Data Engineer Role at Remo Health
What are the primary responsibilities of a Data Engineer at Remo?

As a Data Engineer at Remo, your main responsibilities include managing the full lifecycle of data, designing and maintaining robust ETL pipelines, and optimizing SQL queries for data warehousing. You’ll actively collaborate with data scientists and analysts to ensure data availability and integrity across the organization, empowering all departments to leverage data effectively.

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What qualifications are required for the Data Engineer position at Remo?

To qualify for the Data Engineer role at Remo, candidates should have at least 3 years of experience in data engineering and a background in healthcare analytics. Mastery of SQL, proficiency in Google Cloud services like BigQuery and Dataflow, and experience with ETL processes are essential. Additionally, familiarity with tools like dbt and a strong understanding of HIPAA compliance will be required.

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What tools and technologies does a Data Engineer use at Remo?

At Remo, the Data Engineer utilizes various tools and technologies, including Fivetran for data ingestion, Google Cloud Composer for workflow orchestration, and BigQuery for data analysis. You will also work with data transformation and modeling tools such as dbt, and scripting languages like Python to automate data processing tasks.

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How does the Data Engineer role contribute to Remo's mission?

The Data Engineer plays a crucial role in Remo's mission by ensuring that data is collected, processed, and analyzed efficiently. By developing robust data pipelines and analytical models, you empower the Remo team to make data-driven decisions that enhance the quality and accessibility of dementia care services for families and caregivers.

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Is experience in the healthcare industry required for the Data Engineer role at Remo?

Yes, experience in the healthcare industry is required for the Data Engineer position at Remo. Ideal candidates should have a solid background in healthcare analytics, specifically in building and maintaining ETL processes and engaging in tasks related to forecasting and cohort analysis using healthcare data.

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Common Interview Questions for Data Engineer
Can you describe your experience with ETL processes in your previous Data Engineer roles?

When answering this question, provide specific examples of ETL tools you've used, describe the scope of the projects, and highlight any challenges you faced and how you overcame them. Emphasize your hands-on experience with tools like Fivetran, Apache Airflow, or others relevant to the role.

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What strategies do you use to optimize SQL queries?

To effectively answer, describe techniques such as indexing, partitioning, and writing efficient joins. Share specific instances where you improved query performance, and explain how these optimizations contributed to better data management at your previous job.

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How do you ensure data compliance with regulations like HIPAA?

Discuss your approach to data governance and compliance, including the frameworks and tools you've used. Explain how you handle Protected Health Information (PHI) securely and provide examples of how you've maintained compliance in previous roles.

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What role do you think a Data Engineer plays in collaboration with data scientists?

Highlight your understanding of the teamwork dynamic between Data Engineers and Data Scientists. You could explain how a Data Engineer sets the foundation by providing clean, processed data, allowing Data Scientists to focus on building models and deriving insights.

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Can you explain a challenging data pipeline you built and what you learned from the experience?

Share a specific project that involved complex data transformations or integrations. Discuss the challenges faced during implementation, the solutions you developed, and any lessons learned that you would apply to future projects.

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How do you prioritize tasks when managing multiple data projects?

When addressing this question, describe your methodology for prioritizing tasks—whether through urgency, impact, or resource availability. Illustrate with examples of how you successfully handled competing deadlines in past positions.

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What BI tools have you worked with and how have you used them?

Share your experience with BI tools like Tableau or Power BI, providing examples of reports or dashboards you've created. Discuss how these tools contributed to decision-making processes in your past roles.

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Describe your experience with Google Cloud technologies.

Highlight your hands-on experience with Google Cloud services, such as BigQuery, Dataflow, and Composer. Mention specific projects where these technologies were utilized and how they benefited the overall data strategy.

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How do you handle missing data in datasets?

Demonstrate your problem-solving skills by discussing methods employed to deal with missing data, such as imputation techniques, data augmentation, or working with other departments to source missing information.

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What is your approach to documenting data models and processes?

Emphasize the importance of documentation in data engineering. Discuss how you ensure clear documentation for data models, ETL processes, and data governance practices, including tools and formats you've used.

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Full-time, remote
DATE POSTED
December 11, 2024

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