Papigen
Senior Data Analyst - Power BI | Azure | Data Governance
Papigen, Washington, District Of Columbia, United States
Job Description
Job Description
About Company
Papigen
is a fast-growing global technology services company, delivering innovative digital solutions through deep industry experience and cutting-edge expertise. We specialize in technology transformation, enterprise modernization, and dynamic areas like Cloud, Big Data, Java, React, DevOps, and more. Our client-centric approach combines consulting, engineering, and data science to help businesses evolve and scale efficiently. Role Overview
We are seeking a skilled
Data Analyst
to support enterprise data management, governance, analytics, and reporting initiatives. The role focuses on
data analysis, data modeling, BI dashboard development, and data quality validation
to help deliver a scalable, governed, and insight-driven data environment. The analyst will collaborate closely with business stakeholders, data engineers, and governance teams to unify and enhance the organization’s data assets. Key Responsibilities
Data Analysis Requirements Gathering
– Work with business users to define reporting requirements, KPIs, and data quality rules.
Data Modeling
– Design and validate logical and physical data models across domains for consistency and interoperability.
ETL Data Validation
– Collaborate with data engineering teams to validate ETL/ELT outputs, ensure data completeness and accuracy.
Business Intelligence Development
– Build and maintain
Power BI
dashboards, reports, and visualizations for corporate KPIs, forecasting, and operational analytics.
Data Quality Governance
– Profile data, identify anomalies, and support the remediation process in alignment with governance policies.
Metadata Management
– Support cataloging activities in
Collibra
or
Microsoft Purview , including lineage, classifications, and glossary updates.
Advanced Analytics Support
– Assist with exploratory analysis, statistical modeling, and data preparation for machine learning initiatives.
User Enablement
– Provide training and support for self-service analytics, ensuring governed access and usability.
Collaboration
– Partner with cross-functional teams (engineering, governance, BI, business units) to deliver high-quality data solutions.
Requirements
7+ years
of experience as a
Data Analyst
in data-centric environments.
Strong SQL skills for data querying, validation, and analysis.
Proven experience with
Power BI
(DAX, Power Query, data modeling).
Familiarity with
Azure Data Services
(Azure SQL, Azure Synapse, ADLS).
Understanding of data governance and metadata management tools (e.g.,
Collibra ,
Microsoft Purview ).
Experience in data profiling, quality assessment, and validation techniques.
Exposure to ETL/ELT processes and collaboration with data engineering teams.
Excellent analytical, problem-solving, and communication skills.
Nice to Have Experience with
Databricks
for exploratory analysis and transformation.
Familiarity with
predictive/prescriptive
analytics concepts.
Background in working with multiple data types (structured, semi-structured, unstructured).
Knowledge of data marketplace or data catalog implementations.
Job Description
About Company
Papigen
is a fast-growing global technology services company, delivering innovative digital solutions through deep industry experience and cutting-edge expertise. We specialize in technology transformation, enterprise modernization, and dynamic areas like Cloud, Big Data, Java, React, DevOps, and more. Our client-centric approach combines consulting, engineering, and data science to help businesses evolve and scale efficiently. Role Overview
We are seeking a skilled
Data Analyst
to support enterprise data management, governance, analytics, and reporting initiatives. The role focuses on
data analysis, data modeling, BI dashboard development, and data quality validation
to help deliver a scalable, governed, and insight-driven data environment. The analyst will collaborate closely with business stakeholders, data engineers, and governance teams to unify and enhance the organization’s data assets. Key Responsibilities
Data Analysis Requirements Gathering
– Work with business users to define reporting requirements, KPIs, and data quality rules.
Data Modeling
– Design and validate logical and physical data models across domains for consistency and interoperability.
ETL Data Validation
– Collaborate with data engineering teams to validate ETL/ELT outputs, ensure data completeness and accuracy.
Business Intelligence Development
– Build and maintain
Power BI
dashboards, reports, and visualizations for corporate KPIs, forecasting, and operational analytics.
Data Quality Governance
– Profile data, identify anomalies, and support the remediation process in alignment with governance policies.
Metadata Management
– Support cataloging activities in
Collibra
or
Microsoft Purview , including lineage, classifications, and glossary updates.
Advanced Analytics Support
– Assist with exploratory analysis, statistical modeling, and data preparation for machine learning initiatives.
User Enablement
– Provide training and support for self-service analytics, ensuring governed access and usability.
Collaboration
– Partner with cross-functional teams (engineering, governance, BI, business units) to deliver high-quality data solutions.
Requirements
7+ years
of experience as a
Data Analyst
in data-centric environments.
Strong SQL skills for data querying, validation, and analysis.
Proven experience with
Power BI
(DAX, Power Query, data modeling).
Familiarity with
Azure Data Services
(Azure SQL, Azure Synapse, ADLS).
Understanding of data governance and metadata management tools (e.g.,
Collibra ,
Microsoft Purview ).
Experience in data profiling, quality assessment, and validation techniques.
Exposure to ETL/ELT processes and collaboration with data engineering teams.
Excellent analytical, problem-solving, and communication skills.
Nice to Have Experience with
Databricks
for exploratory analysis and transformation.
Familiarity with
predictive/prescriptive
analytics concepts.
Background in working with multiple data types (structured, semi-structured, unstructured).
Knowledge of data marketplace or data catalog implementations.