Senior Data Engineer

Socium - Teams Done Differently; Taguig; On-site; PHP 1,000,000 - 1,800,000; Full time

Job summary

Socium - Teams Done Differently seeks an experienced Data Engineer to design and optimize scalable data solutions using Python, SQL, and cloud services.

You will build ETL pipelines, models, and orchestrations with Airflow/DBT, collaborating across teams to improve data products and reliability.

Join a multinational technology and consulting environment focused on modern data platforms.

Qualifications

• 5+ years of experience as a Data Engineer.
• Strong Python and SQL skills.
• Knowledge of OLTP/OLAP concepts and data modeling.
• Experience building data pipelines, ETL processes, and data infrastructure.
• Hands-on experience with Apache Airflow and DBT for workflow automation and transformations.
• Experience with Kafka/Pub/Sub, PySpark, or Dataflow.
• Strong analytical and problem-solving skills with excellent communication and collaboration.
• Understanding of cloud migration strategies and best practices.

Responsibilities

• Design, develop, and maintain ETL/data pipelines from various sources into data warehouses.
• Design data models aligned with business needs for efficient querying and analysis.
• Ensure data orchestration pipelines are reliable, scalable, and efficient.
• Collaborate with data teams, vendors, and stakeholders to improve data products, processes, and systems.
• Follow data engineering best practices across coding, DevOps, documentation, and metadata.
• Document current and future solution designs.

Skills

5+ years experience

Python

SQL

OLTP/OLAP

ETL pipelines

Airflow

DBT

Kafka

PySpark

Dataflow

Cloud experience

CI/CD

Analytics tools

Tools

Apache Airflow

DBT

Kafka

Pub/Sub

PySpark

Dataflow

Job description

We are looking for experienced Data Engineers with strong Python, SQL and cloud experience. Join a multinational technology and consulting company and work on modern, scalable data solutions.

Key Job Responsibilities

• Design, develop, and maintain ETL/data pipelines from various sources into data warehouses.
• Design data models aligned with business needs for efficient querying and analysis.
• Ensure data orchestration pipelines are reliable, scalable, and efficient.
• Collaborate with data teams, vendors, and stakeholders to improve data products, processes, and systems.
• Follow data engineering best practices across coding, DevOps, documentation, and metadata.
• Work with audience tracking and subscriber datasets.
• Own assigned work, including development, testing, and delivery.
• Evaluate architectural and data modeling options, considering trade-offs and scalability.
• Maintain high-quality engineering output while meeting project timelines.
• Document current and future solution designs.

Key Job Requirements

• 5+ years of experience as a Data Engineer.
• Strong Python and SQL skills.
• Knowledge of OLTP/OLAP concepts and data modeling.
• Experience building data pipelines, ETL processes, and data infrastructure.
• Hands-on experience with Apache Airflow and DBT for workflow automation and transformations.
• Experience with Kafka/Pub/Sub, PySpark, or Dataflow.
• Strong analytical and problem-solving skills with excellent communication and collaboration.
• Understanding of cloud migration strategies and best practices.
• Experience with GCP, AWS, or Azure for data storage, processing, and analytics.
• Experience with cloud deployment and CI/CD/test automation.
• Familiarity with consumer behavior and/or subscriber data such as Google Analytics, Adobe Analytics, or Snowplow.
• Proficient use of AI tools to improve efficiency and focus on higher-impact technical work