The Role
The Senior Data Engineer will design and maintain ETL/ELT pipelines, manage data sets, and collaborate with ML Engineers on data products.
Summary Generated by Built In
Provectus, a leading AI consultancy and solutions provider specializing in Data Engineering and Machine Learning. With a focus on helping businesses unlock the power of their data, we leverage the latest technologies to build innovative data platforms that drive results. Our Data Engineering team consists of top-tier professionals who design, implement, and optimize scalable, data-driven architectures for clients across various industries.
We are seeking a talented and experienced Data Engineer to join our team at Provectus. As part of our diverse practices, including Data, Machine Learning, DevOps, Application Development, and QA, you will collaborate with a multidisciplinary team of data engineers, machine learning engineers, and application developers.
Responsibilities:
- Collaborate closely with clients to deeply understand their existing IT environments, applications, business requirements, and digital transformation goals.
- Collect and manage large volumes of varied data sets.
- Work directly with ML Engineers to create robust and resilient data pipelines that feed Data Products.
- Define data models that integrate disparate data across the organization.
- Design, implement, and maintain ETL/ELT data pipelines.
- Perform data transformations using tools such as Spark, Trino, and AWS Athena to handle large volumes of data efficiently.
- Develop, continuously test, and deploy Data API Products with Python and frameworks like Flask or FastAPI.
Requirements:
- Experience handling real-time and batch data flow and data warehousing with tools and technologies like Airflow, Dagster, Kafka, Apache Druid, Spark, dbt, etc.
- Experience in AWS.
- Proficiency in programming languages relevant to data engineering, such as Python and SQL.
- Proficiency with Infrastructure as Code (IaC) technologies like Terraform or AWS CloudFormation.
- Experience in building scalable APIs.
- Familiarity with Data Governance aspects like Quality, Discovery, Lineage, Security, Business Glossary, Modeling, Master Data, and Cost Optimization.
- Upper-Intermediate or higher English skills.
- Ability to take ownership, solve problems proactively, and collaborate effectively in dynamic settings.
Nice to Have:
- Experience with Cloud Data Platforms (e.g., Snowflake, Databricks).
- Experience in building Generative AI Applications (e.g., chatbots, RAG systems).
- Relevant AWS, GCP, Azure, Databricks certifications.
- Knowledge of BI Tools (Power BI, QuickSight, Looker, Tableau, etc.).
- Experience in building Data Solutions in a Data Mesh architecture.
We offer:
- Participate in internal training programs (Leadership, Public Speaking, etc.) with full support for AWS and other professional certifications.
- Work with the latest AI tools, premium subscriptions, and the freedom to use them in your daily work.
- Long-term B2B collaboration.
- 100% remote — with flexible hours.
- Collaboration with an international, cross-functional team.
- Comprehensive private medical insurance or budget for your medical needs.
- Paid sick leave, vacation, and public holidays.
- Equipment and all the tech you need for comfortable, productive work.
- Special gifts for weddings, childbirth, and other personal milestones.
Top Skills
Airflow
Apache Druid
Aws Athena
Aws Cloudformation
Dagster
Dbt
Kafka
Python
Spark
SQL
Terraform
Trino
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The Company
What We Do
Provectus is an Artificial Intelligence consultancy and solutions provider, helping businesses achieve their objectives through AI.
We are recognized by industry think tanks as a leading provider of AI solutions in specific business domains, driven by sophisticated IT service management and tech innovation. Provectus is a value driver and a trusted partner for our clients and employees.
Provectus is an AWS Premier Consulting Partner with competencies in Data & Analytics, DevOps, and Machine Learning. We design and build AI solutions for industry-specific use cases, Data and Machine Learning foundation, Cloud transformation, and DevOps adoption.
