The ideal candidate will have a strong background in data engineering, a passion for data architecture, and a proven track record of building scalable data solutions. As a Data Engineer, you will play a critical role in designing, developing, and maintaining our data infrastructure.
Responsibilities:
- Design and implement robust, scalable, and efficient data pipelines and architectures.
- Develop and maintain data models and schemas to support business requirements.
- Integrate data from various sources, including databases, APIs, and third-party data providers.
- Ensure high-quality data integration and transformation processes.
- Manage and optimize large-scale databases and data warehouses.
- Ensure data integrity, security, and performance across all data systems.
- Develop, implement, and maintain ETL processes to support data ingestion and processing.
- Automate and streamline data workflows to improve efficiency and reliability.
- Work closely with data scientists, analysts, and other stakeholders to understand data needs and deliver solutions.
- Collaborate with cross-functional teams to support data-driven decision-making.
- Mentor and provide guidance to junior data engineers.
- Lead by example and contribute to a culture of continuous improvement and innovation.
- Document data engineering processes, data flows, and system configurations.
- Generate reports and dashboards to provide insights into data operations and performance.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.
- 3+ years of experience in data engineering or a related field.
- Proven experience with cloud platforms (e.g., AWS, Azure, Google Cloud).
- Proficiency in SQL, Python, and/or other programming languages.
- Experience with big data technologies (e.g., Hadoop, Spark).
- Strong knowledge of database systems (e.g., MySQL, PostgreSQL, NoSQL databases).
- Familiarity with ETL tools and data pipeline orchestration (e.g., Apache Airflow, Talend).
- Experience with data warehousing solutions (e.g., Redshift, BigQuery, Snowflake).
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
- Ability to work in a fast-paced, dynamic environmen
Preferred Qualifications:
- Experience with machine learning and data science workflows.
- Knowledge of data governance and data quality best practices.
- Familiarity with DevOps and CI/CD practices in data engineering.
