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Mid-Level Data Analyst
GFT Technologies. Build, enhance, and support data solutions in cloud environments.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and maintaining scalable data pipelines, data ingestion, and transformation for analytical purposes, with a strong focus on data quality and governance in cloud environments. Proficient in collaborating with cross-functional teams to implement data solutions that drive business value.
Highest-signal resume keywords
Data Pipeline DevelopmentDatabricks ExperienceAzure Data FactorySQL ProficiencyPython/PySpark Experience
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data IngestionData TransformationData ModelingETL/ELT PracticesData ArchitectureData GovernanceData QualityData AnalysisCloud EnvironmentsData Integration
Soft Skills
Strong Communication SkillsProactive MindsetProblem-Solving OrientationAnalytical ThinkingOrganizational Skills
Tools & Technologies
DatabricksAzure Data FactoryCloud Environments
Certifications & Qualifications
Databricks Certified Data Engineer AssociateDatabricks Certified Data Engineer ProfessionalDatabricks Certified Data Analyst AssociateDatabricks Certified Machine Learning AssociateDatabricks Certified Machine Learning Professional
Industry Keywords
Financial SectorBankingInsuranceAccountingRegulatory ProjectsTax Transformation
Tech Stack
Tools & technologiesAzureCloudETLPySparkPythonSQL
About the role
Key responsibilities & impact- Build, enhance, and support data solutions in cloud environments.
- Ensure data quality, governance, scalability, and performance.
- Develop and maintain scalable and efficient data pipelines.
- Ingest, transform, and make data available for analytical consumption.
- Orchestrate data pipelines and data integration and processing workflows.
- Monitor and optimize data integration and processing workflows.
- Gather requirements and implement data solutions in collaboration with engineering, analytics, and business teams.
Requirements
What you’ll need- Experience developing and maintaining scalable and efficient data pipelines.
- Hands-on experience with data ingestion, transformation, and preparation for analytical consumption.
- Knowledge of data architecture in cloud environments.
- Experience with Databricks for data processing and engineering.
- Experience with Azure Data Factory for pipeline orchestration.
- Advanced knowledge of SQL and data modeling.
- Experience with Python and/or PySpark.
- Experience with cloud environments, preferably Microsoft Azure.
- Knowledge of ETL/ELT practices and data integration.
- Experience monitoring and optimizing data integration and processing workflows.
- Experience working with engineering, analytics, and business teams to gather requirements and implement data solutions.
- Knowledge of data management and data analysis.
- Preferred qualifications: experience with modern data architectures (Data Lake and Lakehouse), data governance and quality, high-volume data environments, projects in the financial, banking, insurance, or accounting sectors, and regulatory and tax transformation projects.
- Databricks certifications are a plus: Databricks Certified Data Engineer Associate; Databricks Certified Data Engineer Professional; Databricks Certified Data Analyst Associate; Databricks Certified Machine Learning Associate; Databricks Certified Machine Learning Professional.
- Enjoy working in a team and collaborating with others.
- Proactive mindset and a strong sense of ownership.
- Problem-solving orientation and commitment to continuous improvement.
- Analytical thinking and the ability to turn data into business value.
- Strong communication skills with technical and business stakeholders.
- Organization and the ability to manage priorities and deadlines.
- Interest in learning new technologies and keeping up with the evolution of the data ecosystem.
Benefits
Comp & perks- Multi-benefit card – choose how and where to use it.
- Scholarships for undergraduate, graduate, MBA, and language courses.
- Certification incentive programs.
- Flexible working hours.
- Competitive salaries.
- Annual performance reviews with a structured career development plan.
- International career opportunities.
- Wellhub and TotalPass.
- Private pension plan.
- Childcare assistance.
- Medical insurance.
- Dental insurance.
- Life insurance.