Senior Data Analytics Engineer

Berlin - Germany

Monthly Salary: Not Disclosed

Posted on: 13 hours ago

Vacancies: 1 Vacancy

Job Summary

As a Senior Analytics Engineer Asset Management your mission is to enable Enpals Asset Management organization with reliable scalable and trusted data models and reporting products. You will build and maintain dbt transformation pipelines create high-quality analytics datasets and support the delivery of asset performance refinancing and portfolio reporting for Germanys largest green energy-tech company.

You will work in a fast-moving environment with changing priorities and complex data sources and you are expected to bring structure ownership and clarity to ambiguous problems.

Build & own analytics foundations for Asset Management

Work closely with stakeholders in Asset Management Finance Accounting and Controlling teams to design build and maintain dbt-based transformation pipelines and analytics-ready data models.
Develop and maintain robust datasets supporting portfolio monitoring asset lifecycle tracking customer agreements refinancing reporting and cashflow/rent payment tracking.
Ensure data models are well-documented tested and reliable enabling self-service usage across the organization.

Enable high-quality reporting & automation

Automate and quality-control recurring reporting processes (monthly/weekly) including asset performance reports used by internal stakeholders and external refinancing partners.
Build long-lasting reporting layers powering Tableau / Power BI / Streamlit dashboards and operational reporting.
Define and implement data quality checks monitoring and validation logic to ensure consistent KPI definitions and trustworthy outputs.

Navigate complex finance operational data landscapes

Develop deep knowledge of Enpals financial and operational systems such as MS Dynamics (ERP) and auxiliary tools (e.g. Aryza Contavio Lucanet Navan Spendesk) ensuring correct interpretation and usage of financial and asset-related data in the Data Warehouse.
Collaborate with system owners and stakeholders to improve upstream data quality and propose enhancements to system usage or data capture processes.

Drive stakeholder alignment & prioritization

Own the project intake process for Asset Management analytics and bring transparency on trade-offs timelines and scope through communication.
Lead regular stakeholder touchpoints (e.g. weekly prioritization meetings) and support quarterly roadmap planning.
Translate business needs into structured work packages and deliver solutions balancing short-term speed with long-term maintainability.

Support analytics maturity & best practices

Coach and support analysts and business users in consuming data through SQL and semantic models enabling a strong self-service culture.
Promote strong engineering standards: version control code reviews modular dbt design and scalable modelling patterns.

Qualifications :

What we need from you

3 years of relevant experience in Analytics Engineering BI Development or Data Engineering ideally in Asset Management Finance Accounting or portfolio-based domains.
Strong expertise in SQL and data modelling with dbt (data modelling marts KPI logic performance tuning).
Familiarity with orchestration and ingestion tooling such as Airflow / Azure Data Factory / Fivetran (or similar).
Exposure to Python for data analysis and automation is a plus.
Experience building reporting layers for Tableau / Power BI / Streamlit (or similar BI tools).
Strong analytical mindset: able to break down ambiguous problems validate business logic and deliver reliable outputs.
Excellent communication skills with the ability to align multiple stakeholder groups and translate requirements into scalable solutions.
High ownership proactive problem-solving mindset and comfort working in a dynamic rapidly changing environment.

Remote Work :

Employment Type :

Full-time

You will work in a fast-moving environment with changing priorities and complex data sources and you are expected to bring structure ownership and clarity to ambiguous problems.

Build & own analytics foundations for Asset Management

Work closely with stakeholders in Asset Management Finance Accounting and Controlling teams to design build and maintain dbt-based transformation pipelines and analytics-ready data models.
Develop and maintain robust datasets supporting portfolio monitoring asset lifecycle tracking customer agreements refinancing reporting and cashflow/rent payment tracking.
Ensure data models are well-documented tested and reliable enabling self-service usage across the organization.

Enable high-quality reporting & automation

Automate and quality-control recurring reporting processes (monthly/weekly) including asset performance reports used by internal stakeholders and external refinancing partners.
Build long-lasting reporting layers powering Tableau / Power BI / Streamlit dashboards and operational reporting.
Define and implement data quality checks monitoring and validation logic to ensure consistent KPI definitions and trustworthy outputs.

Navigate complex finance operational data landscapes

Develop deep knowledge of Enpals financial and operational systems such as MS Dynamics (ERP) and auxiliary tools (e.g. Aryza Contavio Lucanet Navan Spendesk) ensuring correct interpretation and usage of financial and asset-related data in the Data Warehouse.
Collaborate with system owners and stakeholders to improve upstream data quality and propose enhancements to system usage or data capture processes.

Drive stakeholder alignment & prioritization

Own the project intake process for Asset Management analytics and bring transparency on trade-offs timelines and scope through communication.
Lead regular stakeholder touchpoints (e.g. weekly prioritization meetings) and support quarterly roadmap planning.
Translate business needs into structured work packages and deliver solutions balancing short-term speed with long-term maintainability.

Support analytics maturity & best practices

Coach and support analysts and business users in consuming data through SQL and semantic models enabling a strong self-service culture.
Promote strong engineering standards: version control code reviews modular dbt design and scalable modelling patterns.

Qualifications :

What we need from you

3 years of relevant experience in Analytics Engineering BI Development or Data Engineering ideally in Asset Management Finance Accounting or portfolio-based domains.
Strong expertise in SQL and data modelling with dbt (data modelling marts KPI logic performance tuning).
Familiarity with orchestration and ingestion tooling such as Airflow / Azure Data Factory / Fivetran (or similar).
Exposure to Python for data analysis and automation is a plus.
Experience building reporting layers for Tableau / Power BI / Streamlit (or similar BI tools).
Strong analytical mindset: able to break down ambiguous problems validate business logic and deliver reliable outputs.
Excellent communication skills with the ability to align multiple stakeholder groups and translate requirements into scalable solutions.
High ownership proactive problem-solving mindset and comfort working in a dynamic rapidly changing environment.

Remote Work :

Employment Type :

Full-time

Key Skills

Apache Hive
S3
Hadoop
Redshift
Spark
AWS
Apache Pig
NoSQL
Big Data
Data Warehouse
Kafka
Scala

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About Company

Enpal B.V.

As the market leader in the PV (photovoltaic) sector in Germany, Enpal has now installed nearly 70,000 solar systems on rooftopsa feat recognized by some of the most prominent investors worldwide. This achievement has made us the first European start-up in the renewable energy sector ... View more

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