Senior Data Engineer

Introduction A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. Your Role And Responsibilities Data Engineering & Solution Delivery Build and maintain scalable data pipelines, ingestion frameworks, and ELT/ETL processes using modern cloud technologies. Implement ingestion and CDC patterns using tools like Fivetran, Qlik Replicate, or native cloud services. Develop transformation logic using SQL, dbt, Python, and DataOps best practices. Engineer data models across Dimensional, Data Vault, Lakehouse, and semantic layers. Optimize pipelines for performance, reliability, cost efficiency, and scalability. Platform Engineering Develop and optimize cloud-native data platforms (Snowflake, Databricks, AWS, Azure, GCP). Implement warehouse/lakehouse structures, storage standards, governance rules, and data quality frameworks. Leverage orchestration tools such as Airflow, dbt Cloud, or native cloud schedulers to deploy and operate pipelines. Consulting & Client Partnership Engage with client technical and business teams to gather requirements, define solutions, and ensure clarity. Communicate progress, blockers, and recommendations clearly and professionally. Participate in architecture reviews and support Solution Architects in defining best-fit approaches. Serve as a trusted advisor during delivery, balancing technical execution with client expectations. Data Governance, Quality & Security Implement data validation, observability, and monitoring frameworks to ensure trust and reliability. Apply RBAC, data classification, masking, encryption, and compliance best practices. Document technical solutions, lineage, standards, and handover materials. Mentorship & Team Leadership Support and mentor junior and mid-level engineers, promoting Hakkoda’s engineering standards and delivery excellence. Conduct code reviews, provide technical guidance, and contribute to team continuous improvement. Collaborate on internal accelerators, reusable templates, and Hakkoda-branded methodologies. Innovation & Continuous Learning Stay current with emerging technologies across Snowflake, Databricks, AI/ML, streaming platforms, and modern data tooling. Contribute to internal communities of practice, accelerators, and thought leadership. Share learnings and promote a culture of experimentation and continuous improvement. Preferred Education Bachelor's Degree Required Technical And Professional Expertise Required technical and professional expertise 5 years of experience in Data Engineering or related technical roles. Strong SQL expertise and experience with ELT/ETL pipeline development. Hands-on experience with at least one major cloud platform (AWS, Azure, GCP). Good experience with modern data platforms (Snowflake, Databricks, BigQuery, Redshift, Synapse). Proficiency in Python or similar languages for data engineering tasks. Knowledge of data modeling (Dimensional, Data Vault, Lakehouse). Experience with CICD workflows and version control (GitHub, Bitbucket). Consulting or client-facing delivery experience. Preferred Technical And Professional Experience Cloud Integration Knowledge: Exposure to integrating cloud computing concepts and technologies with Snowflake platforms, enhancing data and AI use case implementation. Advanced Data Engineering: Experience working with data engineering principles and practices to deliver high-quality solutions on Snowflake platforms, leveraging expertise in Snowflake and cloud computing. Technical Solution Optimization: Experience applying technical expertise to optimize solutions on Snowflake platforms, ensuring seamless integration and optimal performance for data and AI use cases. English C1