Senior Data Engineer

Fusemachines; Teletrabalho; BRL 386.000 - 497.000; Tempo integral

Resumo da oferta

An innovative AI company is seeking a Senior Data Engineer to architect scalable data solutions. Candidates should bring over 5 years of data engineering experience, with strong proficiency in Python and SQL. You will manage cloud resources, develop ETL processes, and mentor junior engineers. This remote position allows you to work from Brazil while collaborating with a diverse team committed to AI transformation.

Qualificações

• Minimum of 5 years of hands-on data engineering experience.
• Strong proficiency in Python and SQL.
• Expert knowledge in data modeling and architectures.

Responsabilidades

• Architect, design, and implement scalable data solutions.
• Manage cloud resources and workloads for performance.
• Lead development of ETL/ELT processes.

Conhecimentos

Data Engineering

Python

SQL

PySpark/Apache Spark

ETL/ELT

Git workflows

CI/CD

Cloud Technologies

Formação académica

Bachelor's degree in Computer Science or related field

Ferramentas

AWS

GCP

Azure

Snowflake

Databricks

Airflow

dbt

Descrição da oferta de emprego

About Fusemachines

Fusemachines is a 10+ year old AI company, dedicated to delivering state-of-the-art AI products and solutions to a diverse range of industries. Founded by Sameer Maskey, Ph.D., an Adjunct Associate Professor at Columbia University, our company is on a steadfast mission to democratize AI and harness the power of global AI talent from underserved communities. With a robust presence in four countries and a dedicated team of over 400 full-time employees, we are committed to fostering AI transformation journeys for businesses worldwide. At Fusemachines, we not only bridge the gap between AI advancement and its global impact but also strive to deliver the most advanced technology solutions to the world.

Type: Remote Full-time

Senior Data Engineer

Are you an experienced Data Engineering professional with a passion for building scalable, reliable, and high-performance data systems? Do you have hands‑on experience designing and optimizing end‑to‑end real‑time and batch pipelines, and developing cloud‑native data architectures using modern technologies such as AWS, GCP, Azure, Databricks, and Snowflake?

Qualification & Skill Set Requirements

Core Technical Competencies

• Experience: 5+ years of hands‑on data engineering experience in a production environment.
• Languages: Strong proficiency in Python, SQL (complex queries, performance tuning), and PySpark/Apache Spark.
• Data Modeling: Expert knowledge of data modeling (3NF, Star, Snowflake Schema) and Lakehouse/Warehouse architectures.
• ETL/ELT & Orchestration: Proven experience building pipelines using tools like dbt, Airflow, Dagster, or native cloud orchestrators (Glue, Data Factory, Composer).
• Integrations: Experienced in integrating data from diverse sources: APIs, RDBMS/NoSQL databases, flat files, and streaming platforms (Kafka, Kinesis, Pub/Sub).

Cloud Platform Expertise (Specialization‑Specific)

• Snowflake: SnowSQL, Streams, Tasks, Snowpark, and cost optimization.
• Databricks: Delta Lake, Unity Catalog, Delta Live Tables (DLT), and Spark optimization.
• GCP: BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Functions.
• Azure: Synapse Analytics, Data Factory, Azure Databricks, and Stream Analytics.
• AWS: Redshift, S3, Lake Formation, Glue, and Lambda.

Professional Practices

• SDLC & DevOps: Proficient in Git workflows, CI/CD pipelines (GitHub Actions, Azure DevOps, AWS CodePipeline), and IaC (Terraform/CloudFormation).
• Data Governance: Strong understanding of data quality, lineage, observability, security (RBAC, encryption), and compliance frameworks.
• Agile: Active experience in Agile/Scrum environments using Jira or Azure Boards.
• Mentorship: Ability to lead projects and provide technical guidance to junior/mid-level engineers.

Responsibilities

• Architecture: Architect, design, and implement scalable, reliable data solutions and pipelines aligned with business analytics needs.
• Optimization: Manage and fine‑tune cloud resources and workloads for maximum performance, reliability, and cost‑efficiency.
• Data Transformation: Lead the development of ETL/ELT processes for both batch and real‑time data processing.
• Collaboration: Partner with Product, Engineering, and Data Science teams to deliver effective, data‑driven solutions.
• Governance & Quality: Promote and enforce best practices in data governance, security, and data quality frameworks.
• Mentorship: Provide technical leadership and mentorship to the team, ensuring architecture quality and best practices.
• Documentation: Maintain comprehensive documentation of data architectures, configurations, and workflows.

Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.