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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing, maintaining, and optimizing data pipelines using SQL, Python, and PySpark, while ensuring data quality and integrity through effective monitoring and validation processes. Proficient in collaborating with cross-functional teams to implement DataOps practices and improve data solutions.
Highest-signal resume keywords
SQL ExpertisePython ProgrammingDatabricks ProficiencyETL/ELT ProcessesData Quality Assurance
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 Pipeline DevelopmentData IntegrationData AnalysisLog AnalysisRoot-Cause IdentificationData ValidationTechnical DiagnosisData ModelingVersion ControlChange Management
Soft Skills
Strong Communication SkillsOrganizational SkillsAttention to DetailCollaborative Work
Tools & Technologies
DatabricksApache SparkGitAzure DevOps
Industry Keywords
DataOpsMedallion ArchitectureFinOpsData QualityOperational Failures
Tech Stack
Tools & technologiesApacheAzureCloudETLPySparkPythonSparkSQL
About the role
Key responsibilities & impact- Handle and resolve data-related tickets involving pipelines, dashboards, integrations, and processing routines.
- Monitor data processes, identify failures and anomalies, investigate root causes, and implement solutions to reduce recurrence.
- Analyze and resolve moderately complex incidents, including technical diagnosis, log analysis, data validation, and root-cause identification.
- Execute and support deployment processes across development, staging, and production environments.
- Publish, update, and maintain dashboards, ensuring connections, queries, filters, permissions, and refreshes are properly configured.
- Develop, maintain, and optimize data pipelines in Databricks using SQL, Python, and PySpark.
- Implement and improve data ingestion, transformation, processing, and delivery processes.
- Develop and maintain integrations with APIs, databases, files, and internal or external systems.
- Validate data consistency, integrity, and quality, and implement control mechanisms.
- Analyze the performance and efficiency of data processes and implement technical improvements.
- Develop moderately complex data solutions, including ETL/ELT pipelines, queries, models, reports, and dashboards.
- Support corrective and evolutionary maintenance, automation, and the reduction of operational activities.
- Contribute to DataOps practices, version control, change management, and deployment standardization.
- Document solutions, processing rules, dependencies, configurations, and operational procedures.
- Track support metrics, incident recurrence, and SLA compliance.
- Collaborate with Data Engineering, BI, Governance, and business teams.
- Share technical knowledge and contribute to best practices.
Requirements
What you’ll need- Bachelor’s degree in Information Technology, Data Science, Engineering, Information Systems, or a related field.
- Professional experience analyzing, developing, maintaining, or supporting data solutions.
- Strong SQL skills for complex queries, information validation, inconsistency investigation, and data analysis.
- Professional experience using Python for data manipulation, transformation, and processing.
- Knowledge of ETL/ELT processes, data integration, and pipeline development.
- Experience with or practical knowledge of Databricks and the Apache Spark ecosystem, preferably PySpark.
- Knowledge of relational databases, data structures, and data modeling techniques.
- Experience investigating and resolving incidents, analyzing failures, and identifying root causes.
- Knowledge of code version control and change management practices using Git and/or Azure DevOps.
- Ability to develop solutions independently, analyze problems in a structured manner, and propose technical improvements.
- Strong organizational skills, attention to detail, and commitment to data quality, security, and availability.
- Strong communication skills and the ability to work collaboratively with technical teams and business stakeholders.
- Preferred qualifications: experience supporting and evolving enterprise data platforms; Medallion Architecture; scalable ingestion, transformation, and data delivery solutions; FinOps in cloud data environments; and mechanisms for monitoring, validation, and prevention of operational failures.
Benefits
Comp & perks- Flexible Office – 2 days working from home and 3 days in the office.
- Birthday Day Off – Enjoy your special day your way, plus points in our Marketplace!
- Sul América life insurance.
- Psychological support – Access to a platform with psychologists.
- Office massage services.
- Relaxation room.
- Fresh fruit at the office.
- Meal or food allowance.
- Transportation allowance.
- QultureRocks – Performance and development management platform.
- Inspiring and disruptive culture – A dynamic, collaborative, and innovative environment.
- Internal events and engagement activities.
- Exclusive benefits on commemorative dates.