Data Engineer

About Data Competency at Sollers Consulting

Versatility is key to what Sollers Consulting does in IT. Our Data Competency initiative supports the digital transformation of the financial sector, enabling clients to become truly data-driven companies. Our mission is to ensure robust capabilities for addressing financial sector data-related needs.

As a Data Engineer, you will be instrumental in building and optimizing our clients’ data pipelines and data flows. You will contribute to various data initiatives, ensuring optimal data delivery and high-quality data solutions. This role is ideal for candidates with strong experience in data warehousing and data wrangling, who enjoy both building new data systems from the ground up and enhancing existing ones within a dynamic consulting environment.

Our Promises at Sollers Consulting

• Flexible working and hybrid model: Enjoy flexible working hours and a hybrid home office model (2-3 times per week in the office), fostering a healthy work-life balance.
• Career Advancement: Benefit from a clearly defined career path with opportunities for promotion twice a year and transparent salary forecasts.
• Growth Opportunities: Access a generous training budget for courses and conferences, along with an online course platform for continuous learning.
• Personalized Guidance: Receive support from an internal coach for onboarding, training, and career development, including a budget for shared lunches.
• Social Impact: Participate in Sollers Change Makers, our volunteering program, to contribute to the planet and community.
• Team Collaboration: Engage in numerous teambuilding activities, trips, hobby groups, and cultural events that strengthen teamwork.
• Comfortable Work Environment: Work in great offices located in city centers, featuring chill zones (foosball tables, PS5) and regular team lunches.

About the Data Engineer Role

In this role, you will:

• Work with leading data platforms like Snowflake and Databricks.
• Leverage advanced cloud technologies from Azure and AWS.
• Design, build, and optimize scalable data pipelines for peak performance and reliability.
• Advise clients on the best tools, technologies, and architectural improvements.
• Ensure stringent compliance with data privacy, security, and regulatory standards.
• Collaborate closely with various stakeholders to align technical data solutions with critical business objectives.
• Contribute actively to agile project teams and engage directly with clients.

Skills and Tools You Will Use

You will utilize a broad range of technologies and methodologies, including:

• Partners: Snowflake, Databricks
• Cloud Providers: Azure, AWS
• Data Processing: ETL/ELT data pipelines (batch and stream processing)
• Data Storage: DWH, data lakes, data lakehouses
• Analytics: BI & predictive analytics, AI/ML
• Data Sources: RDBMS, CDC, APIs, data connectors, file systems (structured, semi-structured, unstructured)
• Programming: SQL, Python
• Practices: DataOps, data architecture, data modeling, design patterns

Requirements for a Data Engineer

To succeed in this role, you need:

• Minimum 3 years of experience in data engineering.
• Hands-on experience with ETL/ELT processes and pipeline development.
• Familiarity with diverse data sources (RDBMS, CDC, APIs, connectors, structured/semi-structured/unstructured files).
• Solid understanding of data warehouse modeling concepts.
• Proficiency in SQL and Python.
• Practical experience with PySpark or a similar distributed data processing framework.
• Strong command of English (B2/C1 level).
• Effective communication and teamwork skills.
• Full-time availability.
• Eligibility to work in the European Union.

Nice-to-Haves

The following experience would be a significant advantage:

• Experience in the insurance industry.
• Hands-on knowledge of Snowflake or Databricks.
• Familiarity with Azure Data Factory.
• Familiarity with cloud data stacks (AWS, Azure, or GCP).
• Experience with other data-related tools (e.g., Airflow, Kafka).
• Fluency in French or German.

Key skills/competency

• Data Engineering
• ETL/ELT Processes
• Data Pipelines
• Snowflake Platform
• Databricks Platform
• SQL Proficiency
• Python Programming
• Cloud Computing (Azure/AWS)
• Data Warehousing
• Data Modeling