Title- Data Analyst/BI Engineer
Location- Plano, TX - Hybrid (3 days/week on-site) F2F INTERVIEW
Type- Contract- C2C Works
Duration- 12+ Months
Job Description-
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 needs.
Develop advanced SQL queries, analytical models, and reconciliation logic to investigate, validate, and unify complex datasets.
Use Databricks to engineer, transform, optimize, and operationalize large-scale datasets for analytical consumption.
Build curated, business-ready datasets that serve as trusted sources for analysis, executive reporting, and self-service consumption.
Develop and maintain Power BI dashboards and reports that translate complex data into clear, actionable insights for business and executive stakeholders.
Own analytics solutions end to end, from raw data ingestion and transformation through semantic logic, reporting, visualization, and insight generation.
Transform fragmented and complex data into clear, business-relevant stories and recommendations.
Identify relationships between customers, products, locations, revenue, operational activity, and business performance.
Partner with business stakeholders to understand objectives, define KPIs and metrics, and solve challenging business problems.
Investigate data quality issues, perform root-cause analysis, and implement sustainable fixes in partnership with upstream and downstream teams.
Ensure data lineage, business logic, and transformation rules are documented, scalable, and maintainable.
Improve performance, reliability, and usability of analytical workflows using modern engineering and BI best practices.
Continuously expand business, source system, platform, and reporting knowledge to accelerate problem-solving and improve analytical effectiveness.
What Makes Someone Successful in This Role
The strongest individuals in this role are not simply SQL developers, report builders, or dashboard creators. They are end-to-end problem solvers who can connect business needs, data engineering, analytics, and reporting into scalable solutions.
They:
Possess strong analytical curiosity and a desire to deeply understand how the business works.
Have hands-on experience with Databricks, modern data transformation, and analytical data engineering.
Have strong Power BI skills and know how to turn complex analysis into intuitive, executive-friendly dashboards and reporting.
Can connect disparate pieces of information into a complete, accurate, and actionable story.
Are comfortable working through ambiguity and incomplete requirements.
Ask thoughtful questions and challenge assumptions.
Take ownership of finding the right answer, not just the quickest answer.
Understand that trusted analytics begin with well-engineered, validated, and well-modeled data.
Can move seamlessly from raw data to business-ready insight and visualization.
Continuously build expertise in business processes, data lineage, system dependencies, and analytical modeling.
Translate complex technical findings into clear business recommendations and executive-ready outputs.
Demonstrate persistence, intellectual curiosity, and a passion for learning.
Balance speed with rigor, ensuring that solutions are both actionable and sustainable.
Qualifications
Required
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 (PBI) for dashboard development, data modeling, visualization, and business reporting.
Strong understanding of data engineering concepts, including data lineage, data quality, transformation logic, and 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 raw data ingestion to reporting, dashboarding, and insight generation.
Excellent communication and stakeholder management skills.
Ability to translate business questions into technical, analytical, and reporting solutions.
Preferred
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.
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