Wavestone is looking to hire a Data Engineer at a manager level to help address strategic and detailed client needs, acting as a trusted advisor to C-level executives and leading hands-on data projects. The role aims to bridge business strategy and technical execution by architecting and delivering robust, scalable data solutions, mentoring teams, and shaping the firm's data consulting offerings to accelerate and enable AI solutions.
Requirements
- Deep hands-on experience designing, building, and optimizing data pipelines and architectures (Python, SQL, Spark, Databricks, Snowflake, Azure, AWS, etc.).
- Experience creating conceptual, logical, and physical data models that leverage different data modeling concepts and methodologies (normalization/denormalization, dimensional typing, data vault methodology, partitioning/embedding strategies, etc.) to meet solution requirements.
- Expertise in architecting and deploying solutions on leading cloud platforms (Azure, AWS, GCP, Snowflake).
- Mastery of data management, MDM, data quality, and regulatory compliance (e.g., IFRS17, GDPR).
- Advanced proficiency in Python, SQL, and modern data engineering tools (e.g., Spark, Databricks, Airflow).
- Experience with cloud data platforms (Azure, AWS, GCP, Snowflake).
- Relevant certifications (e.g., AWS Certified Data Analytics, Azure Data Engineer, Databricks, Snowflake) are a strong plus.
Responsibilities
- Architect and implement enterprise-scale data platforms, pipelines, and cloud-native solutions (Azure, AWS, Snowflake, Databricks, etc.).
- Oversee and optimize ETL/ELT processes, data integration, and data quality frameworks for large, complex organizations.
- Translate business objectives into actionable technical road maps, balancing innovation, scalability, and operational excellence.
- Deep hands-on experience designing, building, and optimizing data pipelines and architectures (Python, SQL, Spark, Databricks, Snowflake, Azure, AWS, etc.).
- Experience creating conceptual, logical, and physical data models that leverage different data modeling concepts and methodologies (normalization/denormalization, dimensional typing, data vault methodology, partitioning/embedding strategies, etc.) to meet solution requirements.
- Expertise in architecting and deploying solutions on leading cloud platforms (Azure, AWS, GCP, Snowflake).
- Mastery of data management, MDM, data quality, and regulatory compliance (e.g., IFRS17, GDPR).
Other
- Lead complex client engagements in data engineering, analytics, and digital transformation, from strategy through hands-on implementation.
- Advise C-level and senior stakeholders on data strategy, architecture, governance, and technology adoption to drive measurable business value.
- Mentor and develop consultants and client teams, fostering a culture of technical excellence, continuous learning, and high performance.
- Drive business development by shaping proposals, leading client pitches, and contributing to thought leadership and market offerings.
- Stay at the forefront of emerging technologies and industry trends in data engineering, AI/ML, and cloud platforms.
- Strategic Data Leadership: Proven ability to set and execute data strategy, governance, and architecture at the enterprise level.
- Executive Stakeholder Management: Ability to communicate and influence at the C-suite and senior leadership level.
