Accountabilities:

Collaborate with solution architects, cloud engineers, and clients to design, develop, and implement scalable data pipelines, data platforms, data lakes, warehouses, and cloud-based architectures.
Translate complex business and technical requirements into secure, scalable, and production-ready data engineering and AI solutions.
Design and deliver enterprise-level machine learning and generative AI solutions using Infrastructure as Code (IaC), automation, and CI/CD practices.
Build, maintain, and optimize cloud-native data architectures and data processing workflows across major cloud platforms.
Develop and maintain reusable, standardized, and repeatable data products and engineering components that can be leveraged across future consulting engagements.
Implement and maintain infrastructure automation using tools such as Terraform, OpenTofu, and CloudFormation.
Work with data warehouses, NoSQL databases, and streaming technologies to support reliable data ingestion, processing, storage, and integration.
Collaborate across engineering teams, particularly with cloud engineers, to ensure seamless delivery and integration of technical solutions.
Mentor and guide junior engineers, sharing technical expertise, promoting best practices, and supporting professional development.
Maintain continuous professional development by staying current with AWS technologies, cloud architecture best practices, and emerging developments in generative AI.
Engage directly with clients, leading technical discussions, managing expectations, and building strong professional relationships.

Requirements

At least 5 years of professional experience in either Data Engineering or AI/Machine Learning, with a minimum of 1 year of experience in the complementary domain.
Strong SQL development skills, including experience with different SQL dialects, stored procedures, Common Table Expressions (CTEs), and complex queries.
Significant programming experience with languages such as Python, Scala, Java, or similar technologies.
Practical experience using source control and version management tools such as Git, GitHub, GitLab, or Bitbucket.
Regular hands-on experience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform (GCP).
Strong experience implementing Infrastructure as Code (IaC) solutions using Terraform, OpenTofu, CloudFormation, or similar tools.
Experience designing and working with data warehouse technologies such as Amazon Redshift, Snowflake, or Google BigQuery.
Knowledge of NoSQL databases and related concepts, including DynamoDB, Cassandra, and Redis.
Experience with data streaming and distributed processing technologies such as Apache Spark, Apache Kafka, or AWS Kinesis.
Ability to work directly with international clients, independently lead technical conversations, communicate complex concepts, set expectations, and establish trust without relying on a project manager.
Strong analytical thinking, problem-solving abilities, and a proactive approach to technical challenges.
Excellent communication and collaboration skills, with the ability to work effectively across distributed and multicultural teams.
Advanced English proficiency to support effective communication with stakeholders working in the US Pacific Time Zone.
Availability to maintain a minimum of six hours of daily working-hour overlap with the US Pacific Time Zone.

Nice to Have

Experience with ETL and data orchestration tools such as Apache Airflow, dbt, AWS Glue, and Fivetran.
Familiarity with machine learning concepts, including random forests, neural networks, and other common ML algorithms.
Practical experience with machine learning frameworks such as scikit-learn, TensorFlow, and PyTorch.
Knowledge of containerization and orchestration technologies, including Docker and Kubernetes.
Experience with data visualization and business intelligence tools such as Amazon QuickSight, Tableau, and Power BI.
AWS certifications or a strong interest in obtaining relevant cloud certifications.
Previous experience delivering generative AI solutions and staying informed about emerging AI technologies.

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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