Senior Data Engineer (English Required)

Job description

Overview

Be among the first 25 applicants.

Work at DaCodes! We are a team of experts in software development and high-impact digital transformation.

For over 10 years, we've created technology and innovation-driven solutions thanks to our team of 220+ talented DaCoders, including developers, architects, UX/UI designers, PMs, QA testers, and more.

Our team integrates into projects with clients across LATAM and the United States, delivering outstanding results.

At DaCodes, you'll accelerate your professional growth by collaborating on diverse projects across various industries and sectors.

Working with us will make you versatile and agile, giving you the opportunity to work with cutting-edge technologies and collaborate with top-level professionals.

Our DaCoders play a crucial role in the success of our business and that of our clients.

You'll become the expert contributing to our projects while gaining access to disruptive startups and global brands.

Does this sound interesting to you?

We're looking for talent to join our team—let's work together!

Responsibilities

• Design, develop, and maintain scalable and efficient data pipelines for batch and real-time processing.
  
  
• Build and optimize data lakes, warehouses, and analytics solutions on cloud platforms (AWS, GCP, or Azure).
  
  
• Implement ETL/ELT workflows using tools such as Apache Airflow, dbt, or Prefect.
  
  
• Ensure data integrity, consistency, and governance through proper architecture and best practices.
  
  
• Integrate data from various sources (structured and unstructured), including APIs, streaming services, and databases.
  
  
• Work with data scientists and analysts to ensure high availability and accessibility of data for analytics and machine learning models.
  
  
• Monitor, troubleshoot, and improve the performance of data pipelines.
  
  
• Implement security best practices for data access, encryption, and compliance.
  
  
• Collaborate with software engineers to integrate data pipelines into applications and services.
  
  
• Stay up to date with the latest trends in big data, cloud technologies, and data engineering best practices.
  
  

Required Qualifications

• 5+ years of experience in data engineering, data architecture, or backend development.
  
  
• Strong expertise in SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB, DynamoDB, etc.).
  
  
• Cloud expertise with AWS (preferred), GCP, or Azure.
  
  
• Proficiency in Python, Java, or Scala for data processing and pipeline development.
  
  
• Experience with big data frameworks like Apache Spark, Hadoop, or Flink.
  
  
• Hands-on experience with ETL/ELT processes and data pipeline orchestration tools (Apache Airflow, dbt, Luigi, or Prefect).
  
  
• Experience with message queues and streaming technologies (Kafka, Kinesis, Pub/Sub, or RabbitMQ).
  
  
• Knowledge of containerization and orchestration tools (Docker, Kubernetes).
  
  
• Strong problem-solving skills and the ability to optimize performance and scalability.
  
  
• English proficiency (B2 or higher) to collaborate with international teams.
  
  

Nice-to-Have Skills (Preferred)

• Experience with data lakehouse architectures (Delta Lake, Iceberg, Hudi).
  
  
• Familiarity with Machine Learning (ML) and AI-related data workflows.
  
  
• Experience with Infrastructure as Code (Terraform, CloudFormation) for managing data environments.
  
  
• Knowledge of data security and compliance regulations (GDPR, CCPA, HIPAA).
  
  

Key Responsibilities

• Design, develop, and maintain scalable and efficient data pipelines for batch and real-time processing.
  
  
• Build and optimize data lakes, warehouses, and analytics solutions on cloud platforms (AWS, GCP, or Azure).
  
  
• Implement ETL/ELT workflows using tools such as Apache Airflow, dbt, or Prefect.
  
  
• Ensure data integrity, consistency, and governance through proper architecture and best practices.
  
  
• Integrate data from various sources (structured and unstructured), including APIs, streaming services, and databases.
  
  
• Work with data scientists and analysts to ensure high availability and accessibility of data for analytics and machine learning models.
  
  
• Monitor, troubleshoot, and improve the performance of data pipelines.
  
  
• Implement security best practices for data access, encryption, and compliance.
  
  
• Collaborate with software engineers to integrate data pipelines into applications and services.
  
  
• Stay up to date with the latest trends in big data, cloud technologies, and data engineering best practices.
  
  

Benefits

• Integration with global brands and disruptive startups
• Remote work/Home office.
  
  You will be informed from the first session if any positions require a hybrid or on-site format.
  
  Don't worry, most are remote!
• Work schedule aligned with your assigned team/project (Client's time zone)
• Monday to Friday work week
• Legal benefits
• Official holidays according to your assigned team/project
• Vacation days (after six months with the company)
• Day off on your birthday
• Major medical insurance
• Life insurance
• Virtual integration events and interest groups
• Meetups with special guests from companies, IT professionals, and prestigious universities
• Constant feedback and performance tracking
• Access to courses and certifications
• Multicultural work teams
• English classes
• Opportunities across our different business lines

Seniority level

• Mid-Senior level

Employment type

• Full-time

Industry

• IT Services and IT Consulting

Required Skill Profession

Bases De Datos, Analítica Y Bi