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Data Engineer
FCamara Consulting & Training. Design, develop, implement, and maintain data pipelines for extracting, transforming, integrating, and delivering information .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and maintaining ETL/ELT pipelines using Python and SQL, with a strong focus on data quality, governance, and integration within cloud environments, particularly AWS. Capable of translating business requirements into technical solutions while collaborating effectively with cross-functional teams.
Highest-signal resume keywords
Python DevelopmentAdvanced SQL KnowledgeETL/ELT Pipeline DevelopmentAWS Cloud ExperienceData Lake and Data Warehouse Architecture
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
PythonSQLETLELTPandasPySparkData ModelingData ProcessingPipeline OrchestrationData Quality
Soft Skills
CollaborationRequirement GatheringTechnical DocumentationStakeholder EngagementContinuous Improvement
Tools & Technologies
AWS GlueAmazon RedshiftAmazon S3Power BITableauLookerGitApache Airflow
Industry Keywords
Financial SectorData GovernanceData CatalogData QualityData Integration
Tech Stack
Tools & technologiesAirflowAmazon RedshiftApacheAWSCloudETLNumpyPandasPySparkPythonSQLTableau
About the role
Key responsibilities & impact- Design, develop, implement, and maintain data pipelines for extracting, transforming, integrating, and delivering information
- Develop ETL/ELT processes, ensuring efficiency, scalability, traceability, and data quality
- Integrate relational databases, APIs, and structured and semi-structured files
- Develop Python and SQL scripts and applications for data extraction, processing, transformation, and manipulation
- Build and optimize data-processing solutions in cloud environments, preferably AWS
- Participate in defining and evolving Data Lake, Data Warehouse, and analytics architectures
- Implement pipeline monitoring, observability, and failure handling
- Apply best practices for security, governance, quality, and data protection in the financial environment
- Identify opportunities for automation and continuous improvement
- Gather and analyze requirements directly with business teams
- Translate functional requirements and business needs into technical specifications and data solutions
- Collaborate with development, architecture, infrastructure, security, and analytics teams
- Document solutions, data flows, transformation rules, and integrations
- Support technical and functional analyses to identify data inconsistencies and opportunities for improvement
Requirements
What you’ll need- Extensive experience developing with Python for data processing, manipulation, and integration
- Advanced SQL knowledge, including complex queries, joins, stored procedures, and query optimization
- Experience with Pandas and PySpark
- Experience with REST APIs, JSON, CSV, and Parquet
- Experience building and maintaining ETL/ELT pipelines
- Knowledge of relational and dimensional data modeling
- Experience with relational databases and analytical storage solutions
- Knowledge of Data Lake and Data Warehouse architectures
- Experience processing large volumes of data
- Knowledge of pipeline orchestration and scheduling
- Familiarity with data quality, cataloging, lineage, and governance
- Experience gathering functional and technical requirements
- Ability to understand business processes and data-related needs
- Ability to transform business requirements into technical solutions
- Experience documenting requirements, business rules, and integration flows
- Ability to lead technical and functional meetings with stakeholders
- Nice to have: Apache Airflow, PySpark, Python, Pandas, NumPy, advanced SQL, AWS Cloud, AWS Glue, Amazon Redshift, Amazon S3, dimensional modeling, and data governance
- Preferred: experience in the financial sector, Power BI, Tableau, Looker, Git, Data Quality, and Data Catalog
Benefits
Comp & perks- Work on strategic business, technology, and customer data projects in the banking sector
- Dynamic environment with distributed architecture and modern technologies
- Use of technologies within the AWS ecosystem
- Development initiatives and social impact programs at FCamara
- Orange Juice tech community
- Professional Training Program
- Leadership School
- Partnerships with NGOs and EdTech companies