Data Engineer

9 hours ago

San Juan, Philippines Dempsey Resource Management Inc. Full time

Job Summary:
We are looking for a skilled Data Engineer to join our team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support business intelligence, analytics, and data science initiatives. You will work closely with data analysts, data scientists, and other stakeholders to ensure the efficient flow and quality of data across systems.

Key Responsibilities:
Design, develop, and manage ETL/ELT pipelines to ingest data from various internal and external sources.
Build and maintain data architectures (databases, data warehouses, data lakes, etc.).
Ensure data quality, integrity, and security throughout the data lifecycle.
Optimize data workflows for performance and scalability.
Collaborate with data analysts and scientists to provide clean, reliable, and structured data for reporting and modeling.
Implement monitoring and logging tools to track pipeline health and performance.
Participate in data modeling, schema design, and documentation of data systems.
Support real-time and batch data processing needs.
Evaluate and recommend new tools and technologies for data management and processing.

Qualifications:
Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
Proven experience as a Data Engineer or in a similar role.
Proficiency in SQL, Python, or Scala.
Experience with data pipeline tools (e.g., Apache Airflow, Talend, Luigi).
Familiarity with data warehousing solutions (e.g., Snowflake, Amazon Redshift, Google BigQuery).
Experience with cloud platforms (AWS, Azure, or GCP) and cloud data tools.
Knowledge of data modeling, schema design, and data governance practices.
Strong analytical, problem-solving, and communication skills.
Preferred Skills:
Knowledge of big data technologies (e.g., Hadoop, Spark, Kafka).
Experience with DevOps or CI/CD tools related to data engineering.
Familiarity with BI tools (e.g., Tableau, Power BI, Looker) is a plus.

Work Schedule:
5 days a week - Onsite
Office Hours: 8:00AM-6:00/7:00AM-5:00PM
2 Days Off (Weekends)

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