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At Aspire, we're looking for a passionate and experienced Data Engineer to join our growing technology team. In this role, you'll design, build, and optimize scalable data platforms that power analytics, reporting, and business-critical decision-making. You'll collaborate with cross-functional teams to develop reliable, high-performance data solutions while leveraging modern cloud technologies and data engineering best practices.
Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
Build and optimize batch and real-time data processing workflows.
Design and implement robust data models, data warehouses, and data lakes.
Integrate data from multiple sources, including APIs, databases, cloud services, and third-party applications.
Ensure data quality, consistency, integrity, and security across the organization's data platforms.
Optimize the performance of data pipelines, SQL queries, and large-scale data processing systems.
Collaborate with Analytics, Business Intelligence, and Data Science teams to deliver trusted datasets for reporting and insights.
Work closely with Software Engineering and DevOps teams to build reliable and scalable data infrastructure.
Implement monitoring, logging, and alerting to ensure data pipeline reliability and operational excellence.
Participate in designing and evolving the organization's data architecture and engineering standards.
Mentor junior data engineers by sharing technical knowledge and promoting engineering best practices.
Document data flows, architecture, and technical implementations to support knowledge sharing and maintainability.
Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field.
5+ years of experience in Data Engineering or a similar role.
Strong expertise in SQL and relational databases such as Oracle, PostgreSQL, SQL Server, and MySQL.
Hands-on experience with Apache Airflow, Apache Kafka, Apache Spark, or similar data engineering technologies.
Strong programming skills in Python, Java, or Scala.
Experience with cloud data warehouse solutions such as Snowflake, Amazon Redshift, Google BigQuery, or Azure Synapse Analytics.
Strong understanding of ETL/ELT processes, data modeling, and data integration best practices.
Experience working with large-scale distributed data systems.
Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
Experience using Git or other version control systems.
Strong analytical, problem-solving, and communication skills.
Experience with real-time streaming technologies such as Kafka, Flink, or Spark Streaming is a plus
Knowledge of modern data lake platforms, including Delta Lake and Databricks is a plus
Experience with Docker and Kubernetes is a plus
Familiarity with BI and visualization tools such as Power BI, Tableau, or Looker is a plus
Experience implementing CI/CD pipelines for data engineering workflows is a plus
Understanding of data governance, security, privacy, and compliance practices is a plus
Experience working in Agile or Scrum environments.
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