Data Analyst Engineer
EDAG Engineering Scandinavia AB
📍 Göteborg
⏰ Heltid
📋 Tillsvidareanställning (inkl. eventuell provanställning)
🗓 Ansök senast 12 juni 2026
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A Data Analyst is responsible for transforming raw data into meaningful insights that support strategic decision‑making across the organization. This role involves collecting, cleaning, analyzing, and visualizing data from multiple sources while collaborating with cross‑functional teams to improve business performance, operational efficiency, and data‑driven outcomes.
Key Responsibilities
Analyze large, complex datasets using SQL, Python, and BI tools to identify trends, patterns, and actionable insights.
Develop interactive dashboards and reports using Power BI, Tableau, or similar visualization platforms to support business stakeholders.
Build and maintain ETL pipelines to ensure accurate, timely, and reliable data flow across systems.
Partner with product, engineering, finance, and operations teams to define data requirements, KPIs, and reporting standards.
Conduct statistical analyses, including A/B testing, forecasting, and predictive modeling, to support business experiments and strategic planning.
Ensure data quality, governance, and compliance with regulatory standards such as HIPAA, GDPR, or industry‑specific frameworks.
Document data processes, business logic, and analytical methodologies to support transparency and reproducibility.
Support automation initiatives by optimizing workflows, reducing manual reporting, and improving data accessibility.
Required Skills & Qualifications
Strong proficiency in SQL, Python, and data visualization tools (Power BI, Tableau).
Experience with ETL tools and cloud data platforms such as Snowflake, AWS, Azure, or Databricks.
Solid understanding of statistical methods, hypothesis testing, and predictive analytics.
Ability to translate business questions into analytical solutions with clear, data‑driven recommendations.
Excellent communication skills with the ability to present insights to technical and non‑technical audiences.
Knowledge of data governance, security, and compliance standards.
Bachelor’s or Master’s degree in Data Analytics, Computer Science, Engineering, Statistics, or a related field.
Preferred Qualifications
Experience with workflow orchestration tools (Airflow, ADF, Jenkins).
Familiarity with APIs, automation, and LLM‑based workflows.
Certifications in cloud platforms (AWS, Azure, GCP).
Background in healthcare, finance, supply chain, or other regulated industries.
Key Responsibilities
Analyze large, complex datasets using SQL, Python, and BI tools to identify trends, patterns, and actionable insights.
Develop interactive dashboards and reports using Power BI, Tableau, or similar visualization platforms to support business stakeholders.
Build and maintain ETL pipelines to ensure accurate, timely, and reliable data flow across systems.
Partner with product, engineering, finance, and operations teams to define data requirements, KPIs, and reporting standards.
Conduct statistical analyses, including A/B testing, forecasting, and predictive modeling, to support business experiments and strategic planning.
Ensure data quality, governance, and compliance with regulatory standards such as HIPAA, GDPR, or industry‑specific frameworks.
Document data processes, business logic, and analytical methodologies to support transparency and reproducibility.
Support automation initiatives by optimizing workflows, reducing manual reporting, and improving data accessibility.
Required Skills & Qualifications
Strong proficiency in SQL, Python, and data visualization tools (Power BI, Tableau).
Experience with ETL tools and cloud data platforms such as Snowflake, AWS, Azure, or Databricks.
Solid understanding of statistical methods, hypothesis testing, and predictive analytics.
Ability to translate business questions into analytical solutions with clear, data‑driven recommendations.
Excellent communication skills with the ability to present insights to technical and non‑technical audiences.
Knowledge of data governance, security, and compliance standards.
Bachelor’s or Master’s degree in Data Analytics, Computer Science, Engineering, Statistics, or a related field.
Preferred Qualifications
Experience with workflow orchestration tools (Airflow, ADF, Jenkins).
Familiarity with APIs, automation, and LLM‑based workflows.
Certifications in cloud platforms (AWS, Azure, GCP).
Background in healthcare, finance, supply chain, or other regulated industries.