It's fun to work in a company where people truly BELIEVE in what they are doing!
Lead Platform Engineer (AWS + Data Engineering)
9-12 months FTC
Amsterdam
Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.
About the Role
We are seeking a seasoned Architect / Lead Platform Engineer to join our team and support a client whose IT landscape is built on AWS. The client has a centralized data lake (named ) that ingests and manages raw, semi-processed and processed data from SAP, CrushFTP, APIs and external vendors. This data layer serves as the data mart for the organization and is integrated with Databricks for self-serve analytics and use-case development. Additionally, multiple AI/ML accounts are used across teams for OLAP, machine learning and visualization workloads.
This role is ideal for someone who thrives in a multi-account AWS environment, has deep expertise in cloud networking and service integrations and enjoys guiding cross-functional teams through strategic planning and solution architecture. The position is advisory-heavy with a hands-on component focused on Databricks and AWS-based data engineering.
What You’ll Do
Act as a strategic advisor to business, IT and network support teams on building scalable data engineering and analytics solutions.
Architect and guide the implementation of data pipelines, ML workflows and analytics platforms across multiple AWS accounts.
Lead the design and implementation of secure, scalable and cost-effective cloud solutions.
Support the build and optimization of use-cases on Databricks and AWS services.
Establish and promote DevOps, GitOps and DevSecOps practices across the platform.
Ensure adherence to industry best practices for cloud architecture, data governance and CI/CD.
Troubleshoot and resolve platform-level issues across distributed systems.
Collaborate with offshore teams to manage and prioritize tasks effectively.
Must Have Skills
Cloud Engineering: Experience with AWS services including IAM, S3, KMS, EC2, ECS, Lambda, DynamoDB, Glue, Step Functions and SageMaker.
Cloud Services & Advisory: Solid understanding of AWS services including S3, EC2, Lambda, Step Functions, Glue, Load Balancers, RDS, Lake Formation and Databricks.
Collaboration & Leadership: Proven ability to work with cross-functional teams and lead offshore teams effectively.
Data Engineering: Experience building distributed applications in Python, PySpark and warehousing; handling high-volume data pipelines. Strong understanding of Databricks, Delta Lake and the best practices around the platform.
Enterprise Patterns: Familiarity with data engineering and data science best practices at scale. Optimization/Data-modelling principles in Databricks based platforms.
Good to Have Skills
Familiarity with DevOps, GitHub Actions for CI/CD workflows.
Experience working in a shared platform architecture with deployments across multiple AWS accounts.
Exposure to GitOps and DevSecOps practices in large-scale environments with federated ownership.
Knowledge of data governance principles and implementation strategies.
Exposure to handing SFTP/CrushFTP based ingress/egress setups.
AWS Certifications (e.g., Solutions Architect, Data Analytics, DevOps Engineer).
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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