Analytics Engineer / DWH Engineer - Mid / Senior level (100% remote-friendly within Poland)

Job Description

The Data Platform is a central piece of the data operations at Docplanner. We are more than a central hub for analytical data across the company : we are responsible for ensuring that every team has the data and tools they need. We serve teams across the whole company, we collaborate to bring the best insights to life together, we bring software development standards to the analytics world.

We are here because we know for a fact that data is crucial to making the healthcare experience more humane.

The Data Platform aims to provide all teams with self-service, flexible, and scalable solutions for their data needs. The platform is being developed to provide easy access, a seamless experience, and allow for autonomous curation, modeling, and reprocessing of data.

Role

We seek a dedicated individual to join our company as the Analytics Engineer for the Analytics Engineering Team, a group dedicated to data modeling, DWH engineering, and web tracking. The Team's mission is to provide both platform-as-a-product solutions for internal customers, but also to serve as an enabler and consultant for their autonomous work.

On the side of data modeling, the Team is accountable for the DWH as an internal customer-facing product as a whole, including overhauling the data model with the newest approach of Data Vault with dbt, designing & building data domains, managing Redshift cluster and more.

The web tracking accountability is to ensure accurate, reliable and consistent collection of data across our diverse platforms and products. The Team owns tracking strategies including tooling and implementation across our products.

Your role will be essential also in the context of Data Governance initiatives : you will focus on designing and enforcing data layering and decentralized ownership, ensuring data integrity to support our decision-making processes.

What you will be doing

Data Platform as a product

You will build a platform for data analytics teams to create and maintain their data models according to best practices and state-of-the-art technologies, in detail :

Build, automate and assure the quality of data products in cooperation with analysts and data engineers.

Own and improve the DWH data model, making it more accessible and easier to use.

Own and maintain the DWH cluster.

Apply expertise in dbt, data domainisation, and Data Vault.

Enabling data analytics in the organization

Acting as a product owner and consultant to data analytics teams, you will ensure the platform's success through proper adoption, engagement, and result, meaning :

Collaborate with analytics teams on building data models for different business areas.

Assure technical guidelines and a big picture view.

Support teams to own their data models and gain autonomy.

Advocate for best practices in data engineering and analytics, ex. by leading workshops and training.

Align data initiatives with business goals.

Proactively communicate with internal stakeholders.

Qualifications

What will help you thrive?

Extensional experience connected with data warehousing and / or database administration.

Expert in SQL, particularly in query optimization and database design.

Strong skills in Python and SQL , following good coding practices.

Strong data modeling skills  (you can name at least five differences between Kimball and Inmon : ))

Deep knowledge of BI, data modeling techniques, and trends (e.g., Data Vault, Kimball, Data Mesh).

Strong project management skills and experience  managing projects end-to-end,  ensuring timely delivery and alignment with business goals.

Excellent communication and interpersonal skills.

Growth mindset : nobody ticks all those boxes above, but a willingness to learn is strongly valued here.

Hands-on experience with orchestrators like Airflow

• or Dagster.

Ability to work collaboratively and adopt  code versioning best practices  (git).

Hands-on experience with cloud technologies  and ETL / ELT tools (one among AWS, GPC, Azure, dbt, dagster, airflow, Luigi).

Good level of English.

Which skills are bonus points?

Hands-on experience with dbt in large-scale deployments.

Knowledge of Spark and Scala language are nice to have.

Aligned with our stack (e.g. : AWS ecosystem, Redshift, S3, Tableau, Superset).

Infrastructure knowledge : Docker, Terraform, Kubernetes, Helm.

Additional Information

Lets talk money

A salary adequate to your experience and skills.

Share options plan after 6 months of working with us.

True flexibility and work-life balance

Remote or hybrid work model with or hub in Warsaw;

Flexible working hours (fully flexible, as in most cases you only have to be on a couple of meetings weekly);

20 / 26 days of paid time off (depending on your contract);

Additional paid day off on your birthday or work anniversary (you choose what you want to celebrate).

Health comes first

Private healthcare plan with iFeel, a technological platform for mental wellness offering online psychological support and counseling.

Keep growing with us

We promote and embrace equal opportunities in our hiring process, and also every day at work. When you apply for our roles you receive equal treatment regardless of age, disabilities, gender reassignment, marital or civil partner status, pregnancy or parental status, race, colour, nationality, ethnic or national origin, religion or belief, sex, sexual orientation or any other dimension of human difference. If you require additional support in your recruitment process, we kindly encourage you to let us know. Behind those words youre reading, theres a person (hi!) who already helped a candidate by adapting the interviews, and now were lucky to have this person with us. So, even if youve never asked for it before, may this serve as a sign that, now, you can do so. We can only truly be equal if we adapt to each other.

We believe all humans, in all their beautiful diversity, should have equal rights, dignity and respect. Period. Mariusz Gralewski, CEO