Senior Analytics Engineer - Databricks / BI

140 - 170 PLN/ godz./ godz.B2BB2B (netto)

SeniorZdalnie·WarszawaFull-time·B2B

#471756·Dodano 5 dni temu·8

Źródło: justjoin.it

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Tech Stack / Keywords

Databricks Python PySpark SQLDelta LakealteryxTableauPower BI

Podsumowanie oferty

Design and maintain cloud-based ETL/ELT workflows, data models, and automated reporting solutions for a long-term initiative serving enterprise brands. Work across data engineering and business intelligence using Databricks, Alteryx, Tableau, and Power BI.

Wymagania

At least 3 years of hands-on experience in analytics engineering, cloud data platforms, and enterprise BI solutions.
Strong proficiency with Databricks, including Python, PySpark, SQL, Delta Lake, and Databricks Workflows.
Hands-on experience with Alteryx for automated ETL, data preparation, and reporting workflows.
Extensive experience developing interactive dashboards and visualisations in Tableau, Power BI, or equivalent enterprise BI tools.
Working knowledge of Microsoft Azure and cloud data architectures.
Practical experience with API integrations, data ingestion pipelines, and workflow orchestration such as Databricks Workflows, Airflow, or Azure Data Factory.
Understanding of dimensional data modelling, semantic layers, data validation, and automated quality checks.
Familiarity with data governance, security standards, and Git-based version control workflows.
Strong analytical problem-solving abilities and clear English communication skills for collaborating with technical and business stakeholders.
Degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, Statistics, or a related field, or equivalent practical experience.

Nice to have:

Familiarity with corporate finance KPIs and revenue metrics.
Experience working with spatial or geospatial datasets.
Exposure to collaborating with Data Science and AI teams on model feature preparation and AI-driven data assets.

Obowiązki

Lead the development and maintenance of reusable, analysis-ready datasets and models for reporting, BI dashboards, and advanced analytics.
Design and implement scalable ingestion and transformation pipelines via APIs and cloud connectors using Alteryx, Databricks SQL, PySpark, and Azure services.
Build, maintain, and enhance interactive dashboards and executive-level visualisations in Tableau and Power BI.
Orchestrate and automate ETL and ELT workflows using tools such as Databricks Workflows, Apache Airflow, or Azure Data Factory.
Own data modelling, semantic layer consistency, and metric definitions to align analytical assets and business KPIs.
Perform data validation, QA, and automated anomaly detection to ensure data integrity, completeness, and reliability.
Troubleshoot data modelling, transformation, and metric discrepancy issues; conduct root cause analysis and provide lasting resolutions.
Maintain technical documentation, source-to-target dependencies, and semantic definitions, applying version control and code review practices.
Collaborate with data analysts, data scientists, AI teams, and client stakeholders to align data engineering deliverables with machine learning and reporting needs.

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