Senior Data Engineer - Scalable Pipelines & Cloud Analytics

We are looking for a talented and motivated Data Engineer to join our growing technology team. The ideal candidate will be responsible for designing, building, optimizing, and maintaining scalable data pipelines and cloud-based data solutions that support analytics, reporting, and machine learning initiatives.

The Data Engineer will work closely with Data Architects, Data Analysts, Data Scientists, Software Engineers, and business stakeholders to ensure high-quality, reliable, and efficient data processing across the organization.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines.
• Build and optimize data architectures, databases, and data lakes/warehouses.
• Develop and maintain integrations between multiple data sources and enterprise systems.
• Ensure data quality, integrity, governance, and security standards are met.
• Optimize data processing performance and troubleshoot pipeline issues.
• Work with cloud platforms such as AWS, Azure, or Google Cloud.
• Collaborate with cross-functional teams to understand business and technical requirements.
• Support analytics and reporting initiatives by providing clean and reliable datasets.
• Implement monitoring, logging, and automation for data workflows.
• Participate in Agile ceremonies and contribute to technical documentation and best practices.
• Advanced conversational English required

Seniority Level

Required Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
• 3+ years of experience as a Data Engineer or in a similar role.
• Strong experience with SQL and relational/non-relational databases.
• Experience building ETL/ELT processes and data pipelines.
• Proficiency in Python, Scala, Java, or similar programming languages.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP).
• Experience with big data technologies such as Spark, Hadoop, Kafka, or Databricks.
• Knowledge of data warehousing concepts and tools such as Snowflake, Redshift, BigQuery, or Synapse.
• Familiarity with CI/CD pipelines, Git, and DevOps practices.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with orchestration tools such as Airflow or Prefect.
• Knowledge of data modeling and data governance practices.
• Experience supporting Machine Learning or AI data environments.
• Certifications in cloud technologies or data engineering are a plus.

Soft Skills

• Strong communication and collaboration skills.
• Ability to work independently and in team environments.
• Detail-oriented with strong organizational skills.
• Proactive mindset and continuous learning attitude.

Detalles