Senior Data Architect

Design, develop, and maintain scalable data pipelines and ETL processes to ingest, transform, and load large volumes of data from diverse sources.

Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and translate them into technical solutions.

Optimize data processing and storage solutions for performance, cost-effectiveness, and scalability in cloud environments (e.g., AWS, Azure, Google Cloud Platform).

Implement data quality checks, monitoring, and alerting mechanisms to ensure the integrity and reliability of our data assets.

Stay abreast of emerging technologies and best practices in data engineering, and recommend innovative solutions to enhance our data infrastructure.

Mentor junior members of the team and contribute to knowledge sharing initiatives to foster a culture of continuous learning and improvement.

Qualifications:

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

8 + years of experience in data engineering roles, with a strong focus on building and optimizing data pipelines in cloud environments.

Proficiency in Python programming and SQL, with experience in developing complex data transformations and querying large datasets.

Hands-on experience with cloud-based data technologies such as AWS (e.g., S3, Glue, Redshift), Azure (e.g., Blob Storage, Data Factory, Databricks), or Google Cloud Platform (e.g., BigQuery, Dataflow, Dataproc).

Solid understanding of distributed computing principles and experience with technologies such as Spark, Hadoop, or similar frameworks.

Strong analytical and problem-solving skills, with a keen attention to detail and a commitment to delivering high-quality solutions.

Excellent communication and collaboration skills, with the ability to work effectively in a fast-paced, cross-functional team environment.