About the role

The role involves designing and maintaining scalable data pipelines and transformation logic to convert complex datasets into actionable business insights. You will also develop advanced analytical models and Power BI dashboards to support executive reporting and decision-making.

What they look for

SQL Databricks Power BI Data Engineering Data Pipelines Data Modeling Data Analysis Data Quality Data Lineage Transformation Logic Analytical Models Stakeholder Management KPI Definition Root-cause Analysis Business Intelligence Reporting

Requirements

Candidates must have strong hands-on experience with SQL, Databricks, and Power BI for large-scale data processing and visualization. A deep understanding of data engineering concepts, including data lineage and quality, is essential for this role.

Full description

Job Title: Data Analyst / Analytics Engineer

Location: Plano, TX (Hybrid — 3 days/week onsite, 2 days remote)

Company Overview

Glint Tech Solutions is a women-owned, global IT staffing and recruiting firm serving enterprise clients across the USA and Canada.

Project Description

A leading enterprise client, a multinational telecommunications technology company, has an urgent need for a Data Analyst / Analytics Engineer to help transform complex, disconnected data into trusted business insights and scalable data solutions.

Key Responsibilities

Analyze and integrate data across multiple applications, source systems, and business domains

Design, build, and maintain scalable data pipelines and transformation logic to support analytics and reporting

Develop advanced SQL queries, analytical models, and reconciliation logic to validate and unify complex datasets

Use Databricks to engineer, transform, optimize, and operationalize large-scale datasets

Build curated, business-ready datasets for analysis, executive reporting, and self-service consumption

Develop and maintain Power BI dashboards and reports for business and executive stakeholders

Own analytics solutions end to end — from raw data ingestion through semantic logic, reporting, and insight generation

Identify relationships between customers, products, locations, revenue, and operational performance

Partner with business stakeholders to define KPIs, metrics, and solve business problems

Investigate data quality issues, perform root-cause analysis, and implement sustainable fixes

Ensure data lineage, business logic, and transformation rules are documented and maintainable

Improve performance, reliability, and usability of analytical workflows

Mandatory Skills

Strong SQL development and data analysis experience

Strong hands-on experience with Databricks for large-scale data processing, transformation, and analytics

Experience designing and maintaining data pipelines, transformation workflows, and curated analytical datasets

Strong experience with Power BI for dashboard development, data modeling, and visualization

Strong understanding of data engineering concepts — data lineage, data quality, transformation logic, scalable data modeling

Experience working with large and complex datasets across multiple systems

Strong problem-solving and analytical skills

Ability to investigate and reconcile data across multiple platforms and source systems

Experience supporting end-to-end analytics, from ingestion to reporting and insight generation

Excellent communication and stakeholder management skills

Ability to translate business questions into technical and reporting solutions

Nice-to-Have Skills

Experience with Snowflake, Python, Spark, Terraform, or enterprise data warehouse environments

Experience with modern cloud-based analytics platforms and data engineering frameworks

Knowledge of telecommunications, customer, revenue, operational, or financial data domains

Experience working with cross-functional teams in a fast-paced environment

Familiarity with KPI governance, executive reporting, and semantic layer design