Data Scientist – Analytics and Data Engineering Support (ITSTM)

Reads like an Analytics Engineer role: dbt models and clean tables.

Sofia, SC-132Mimi Balkanska, Sofia City, Bulgaria

Pay: Pay not listed
Work setting: Hybrid — work setting source
Work setup in the employer’s posting: hybrid remote
From the employer’s posting
Employment: Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

We are seeking a highly motivated Data Scientist with expertise in data analytics, data engineering, and business intelligence to support enterprise transformation initiatives.

Develop and maintain Power BI dashboards and executive reports
Build and optimize data pipelines using Microsoft Fabric, Databricks, SQL, and Python
Analyze operational, transformation, and Agile delivery metrics for insights
Implement Power BI Row-Level Security and data governance standards
Conduct statistical analysis and data modeling to support business decisions

From the employer’s posting

We are seeking a highly motivated Data Scientist with expertise in data analytics, data engineering, and business intelligence to support enterprise transformation initiatives. The ideal candidate will transform complex data into actionable insights, develop scalable reporting solutions, and enable data-driven decision making.

Develop and maintain Power BI dashboards and executive reports.

Build and optimize data pipelines using Microsoft Fabric, Databricks, SQL, and Python.

Analyze operational, transformation, and Agile delivery metrics to generate actionable insights.

Implement Power BI Row-Level Security (RLS) and ensure data governance standards.

Conduct statistical analysis and data modeling to support business decisions.

What you’ll bring

All qualifications

Core experience

Several years of experience in analytics, data engineering, or BI
Strong hands-on experience with Power BI, SQL, Python, and Excel
Experience with Microsoft Fabric, Databricks, and data modeling
Knowledge of Agile methodologies (SAFe, Scrum, Kanban)
Excellent communication, stakeholder management, and problem-solving skills

Qualification wording

Several years of experience in Data Analytics, Data Engineering, or Business Intelligence.

Strong hands-on experience with Power BI, SQL, Python, and Excel.

Experience with Microsoft Fabric, Databricks, and data modeling.

Knowledge of Agile methodologies (SAFe, Scrum, Kanban).

Excellent communication, stakeholder management, and problem-solving skills.

Apply at Cognizant

Posting record

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Status in our records: Live
First seen by us: Sep 24, 202641 days ago
Recorded sightings: 109
Last seen by us: Nov 4, 2026

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Day 41

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From 1,405 similar postings that came down. Coming down is not always a hire.

Cognizant is hiring

140 open jobs

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Hiring at a steady pace
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4% of open jobs were reposted

Hiring record

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Python
SQL
Databricks
Excel
Power BI

Where the posting names them

Key Responsibilities: Develop and maintain Power BI dashboards and executive reports. Build and optimize data pipelines using Microsoft Fabric, Databricks, SQL, and Python. Analyze operational, transformation, and Agile delivery metrics to generate actionable insights. Implement Power BI Row-Level Security (RLS) and ensure data governance standards. Conduct statistical analysis and data modeling to support business decisions. Collaborate with stakeholders across business and technology teams. Leverage AI and automation tools to enhance reporting and operational efficiency. Required Skills:

Required Skills: Several years of experience in Data Analytics, Data Engineering, or Business Intelligence. Strong hands-on experience with Power BI, SQL, Python, and Excel. Experience with Microsoft Fabric, Databricks, and data modeling. Knowledge of Agile methodologies (SAFe, Scrum, Kanban). Excellent communication, stakeholder management, and problem-solving skills. Nice to Have:

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Your next step

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About the role

We file this job under Analytics Engineer, by the work the posting describes.

Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.

Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.

A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Role Overview:

We are seeking a highly motivated Data Scientist with expertise in data analytics, data engineering, and business intelligence to support enterprise transformation initiatives. The ideal candidate will transform complex data into actionable insights, develop scalable reporting solutions, and enable data-driven decision making.

Key Responsibilities:

Develop and maintain Power BI dashboards and executive reports.
Build and optimize data pipelines using Microsoft Fabric, Databricks, SQL, and Python.
Analyze operational, transformation, and Agile delivery metrics to generate actionable insights.
Implement Power BI Row-Level Security (RLS) and ensure data governance standards.
Conduct statistical analysis and data modeling to support business decisions.
Collaborate with stakeholders across business and technology teams.
Leverage AI and automation tools to enhance reporting and operational efficiency.

Required Skills:

Several years of experience in Data Analytics, Data Engineering, or Business Intelligence.
Strong hands-on experience with Power BI, SQL, Python, and Excel.
Experience with Microsoft Fabric, Databricks, and data modeling.
Knowledge of Agile methodologies (SAFe, Scrum, Kanban).
Excellent communication, stakeholder management, and problem-solving skills.

Nice to Have:

SAFe Agile Certification.
Experience supporting digital transformation or enterprise-wide programs.

Source details

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