Octal Technical Solutions

Data Engineer, Hybrid Cloud, Reporting and Visualization

Octal Technical Solutions

full-time

Posted on:

Origin:  • 🇵🇭 Philippines

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Job Level

Mid-LevelSenior

Tech Stack

Amazon RedshiftAWSAzureBigQueryCloudETLGoogle Cloud PlatformPythonSQLTableau

About the role

  • Design, build, and maintain scalable ETL/data pipelines to extract, transform, and load data from databases, APIs, and files into data warehouses or data lakes.
  • Manage and optimize data infrastructure across hybrid cloud environments, leveraging cloud-native services and on-premises resources.
  • Ensure data quality through implementation of data validation, cleansing, and standardization processes.
  • Develop interactive reports and dashboards using tools like Power BI, Tableau, or Looker to provide actionable insights to stakeholders.
  • Adhere to data governance policies and procedures, including data security, privacy, and compliance regulations.
  • Design and implement data models (e.g., dimensional, normalized) to optimize data storage and retrieval.
  • Automate data pipelines and processes using scripting languages (e.g., Python, SQL) and automation tools.
  • Collaborate with data analysts, scientists, and business users to understand requirements and deliver relevant data solutions.

Requirements

  • Proven experience as a Data Engineer or similar role with a focus on data pipelines, cloud infrastructure, and reporting.
  • Strong understanding of data engineering concepts, tools, and technologies (e.g., SQL, Python, ETL tools, cloud platforms).
  • Experience with major cloud platforms (e.g., AWS, Azure, GCP) and their data-related services (e.g., BigQuery, Redshift, data lakes, data pipelines).
  • Proficiency in data modeling techniques (e.g., dimensional, normalized) and data warehouse design.
  • Expertise in using reporting and visualization tools (e.g., Looker, Power BI, Tableau) to create interactive dashboards.
  • Ability to troubleshoot complex data-related issues and find innovative solutions.
  • Excellent communication skills to collaborate effectively with cross-functional teams.
  • Preferred certifications (e.g., AWS Certified Data Engineer, Azure Certified Data Engineer, GCP Certified Professional Data Engineer).
  • Additional preferred skills: experience with data warehousing and data lake technologies (e.g., BigQuery, Redshift, Snowflake, Databricks); knowledge of data analytics and machine learning concepts; familiarity with data governance and compliance frameworks (e.g., HIPAA, GDPR, CCPA).