FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Data Engineer
INNOCV Solutions. Lead the design, development, and maintenance of scalable and efficient cloud data pipelines .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and developing scalable cloud data pipelines and services using Python, with a strong focus on data governance, quality, and compliance. Proficient in implementing robust ETL/ELT processes and collaborating with cross-functional teams to deliver data solutions.
Highest-signal resume keywords
Python Data ProcessingAPI DevelopmentETL/ELT Pipeline DevelopmentCloud Platforms (AWS, Azure, GCP)Data Governance and Compliance
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonETLData IntegrationData WarehousingData LakesSQLNoSQLBig Data TechnologiesData StreamingData Visualization
Soft Skills
CollaborationProblem-SolvingCommunication
Tools & Technologies
DatabricksOpenShiftKafkaBitbucketJiraJenkinsPyTest
Industry Keywords
Financial SectorRegulatory ComplianceData Governance
Tech Stack
Tools & technologiesAWSAzureCloudETLGoogle Cloud PlatformHadoopJavaJenkinsKafkaMongoDBNoSQLNumpyOpenShiftPandasPostgresPySparkPythonSparkSpringSpring BootSpringBootSQL
About the role
Key responsibilities & impact- Lead the design, development, and maintenance of scalable and efficient cloud data pipelines
- Ensure data availability, quality, and governance for strategic decision-making
- Design and develop scalable data pipelines and data services using Python and relevant technologies
- Build and maintain robust, automated ETL/ELT processes with clean, modular, reusable, and maintainable code
- Integrate data from APIs, databases, files, and third-party systems using reliable and fault-tolerant integrations
- Develop APIs and data ingestion services to expose, consume, or orchestrate data across systems
- Apply software engineering practices including version control, code reviews, testing, CI/CD, logging, monitoring, error handling, and documentation
- Optimize data ingestion and transformation performance and scalability
- Identify bottlenecks and improve code and infrastructure
- Collaborate with Data Science, BI, Product, and Software Engineering teams to translate requirements into data solutions
- Design solutions with security, data quality, governance, and regulatory compliance in mind
- Contribute to technical decisions, architecture, data platform evolution, and development standards
- Document technical solutions, APIs, pipelines, and processes for maintainability and knowledge sharing
Requirements
What you’ll need- Strong experience developing in Python, particularly for data processing, transformation, integration, and analytics
- Experience designing, developing, and consuming APIs and data integration services
- Solid software development practices, including clean and maintainable code, version control, code reviews, automated testing, and CI/CD
- Hands-on experience with containers and OpenShift environments
- Strong knowledge of relational databases such as PostgreSQL or SQL Server
- Strong knowledge of NoSQL databases such as MongoDB or Couchbase
- Hands-on experience with cloud platforms and cloud-based data services such as AWS, Azure, or GCP
- Solid understanding of Data Lakes, Data Warehouses, and modern data architectures
- Experience with Python data engineering and analytics libraries, such as Pandas, NumPy, PySpark, and Spark
- Hands-on experience with Databricks, including data engineering, analytics, and scalable data processing solutions
- Knowledge of Big Data technologies, such as Spark or Hadoop
- Experience developing and maintaining ETL/ELT pipelines and data ingestion processes
- Experience with data streaming technologies, such as Kafka
- Experience with data governance, security, and regulatory requirements
- Experience with data visualization tools, such as Matplotlib, Seaborn, or Plotly
- Previous experience in the financial sector or other regulated environments
- Experience with Java and Spring Boot development
- Strong technical English skills
- Experience with DevOps and development tools, including Bitbucket, Jira, Jenkins, and testing frameworks such as PyTest
- Commitment to diversity and inclusion
Benefits
Comp & perks- Professional development through training, tech breakfasts, and attendance at forums
- Personal budget for staying up to date with market trends
- Flexible hours
- Special timetable: Fridays and summer 7h
- Every three years, 6 extra days off
- Day off on your birthday
- Referral benefit for bringing a friend
- Flexible compensation
- Wellness - Gympass
- Volunteering opportunities
- Company events and team buildings
- 42 benefits offered in total
- Work-life balance and flexibility
- Supportive human working environment
- Professional Training & Certifications