Data Engineering Consultant
Accountabilities: As a Data Engineering Consultant, you will lead the design, implementation, and optimization of modern data platforms while providing technical guidance to clients and stakeholders. Your main responsibilities will include:
Designing and delivering scalable data platforms, analytics solutions, and modern data architectures for global clients.
Developing and optimizing data solutions using technologies such as Snowflake, Databricks, Amazon Redshift, and Azure Synapse Analytics.
Building and maintaining efficient ETL/ELT workflows using tools such as Fivetran, Alteryx, and other data integration platforms.
Designing data lake and lakehouse architectures to support batch and real-time data processing requirements.
Working with cloud platforms including AWS, Azure, and GCP to build secure and reliable data environments.
Developing data pipelines, optimizing performance, and ensuring solutions meet scalability and reliability standards.
Applying best practices in data governance, security, compliance, and data quality management.
Collaborating with business leaders, technical teams, and stakeholders to understand requirements and translate them into effective data solutions.
Leading technical discussions, guiding delivery teams, and supporting client-facing consulting engagements.
Contributing to continuous improvement of data engineering standards, methodologies, and solution approaches.
Requirements:
The ideal candidate is a senior data engineering professional with strong consulting experience and expertise in modern data platforms. You should bring:
9+ years of experience in data engineering, data architecture, analytics consulting, or related technology roles.
5+ years of hands-on experience implementing platforms such as Snowflake, Databricks, Amazon Redshift, or Azure Synapse Analytics.
Strong experience with cloud platforms including AWS, Azure, or Google Cloud Platform.
Proven expertise with ETL/ELT tools, including Fivetran, Alteryx, or similar data integration technologies.
Experience designing data lake and lakehouse architectures and supporting both batch and real-time data pipelines.
Advanced SQL skills and strong programming knowledge in Python, including libraries such as Pandas, NumPy, and Matplotlib.
Good understanding of data governance, security practices, and compliance frameworks.
Experience leading teams, technical workstreams, or consulting engagements in global delivery environments.
Strong communication skills with the ability to collaborate with technical teams, business stakeholders, and executive audiences.
Certifications in Snowflake, Alteryx, Power BI, or Tableau are preferred.
SnowPro Advanced Certification is highly desirable.
MBA, Bachelor’s degree, or higher qualification in Engineering, Data Science, Information Systems, Mathematics, or a related field.
Benefits:
The role offers the opportunity to work on complex data transformation initiatives while collaborating with global teams and modern technology platforms. Benefits include:
Fully remote work opportunity.
Opportunity to work on large-scale data engineering and analytics projects.
Exposure to advanced cloud platforms, data architectures, and enterprise technologies.
Professional growth through challenging consulting engagements.
Opportunity to collaborate with technical experts and business stakeholders worldwide.
Continuous learning opportunities through evolving data technologies and industry practices.
How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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