Description:

The role involves designing, building, and maintaining data pipelines that support robust data architectures and facilitate seamless data flow.
The Data Engineer will develop and optimize data systems that drive impactful analytics.
Responsibilities include developing and maintaining data pipelines for data ingestion, transformation, and integration using cloud technologies.
The engineer will manage and optimize data storage solutions, architecting data lakes and warehouses using platforms like BigQuery, Redshift, or Snowflake.
Collaboration with data scientists, analysts, and business stakeholders is essential to align data solutions with business goals.
The role requires ensuring data quality and reliability through validation, error handling, and consistency checks.
The engineer will develop and automate ETL processes to handle complex data transformations.
Monitoring and maintaining data infrastructure is crucial, using tools to track performance and reliability.
Strategies for efficient resource allocation and cost-effective data processing will be implemented.

Requirements:

Candidates must have experience with cloud data platforms such as AWS, GCP, or Azure, demonstrating proficiency in handling cloud-based data solutions.
Proficiency in programming languages such as Python, Java, or Scala is required for building data pipelines and processing tasks.
A proven ability to develop, maintain, and optimize ETL processes is necessary, along with experience using orchestration tools like Apache Airflow or Luigi.
Strong SQL skills and experience with relational and NoSQL databases are essential.
Excellent problem-solving skills and a proactive approach to resolving data-related challenges are required.
A Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field is necessary, with equivalent experience considered.
Certifications in cloud data engineering are a plus.
Candidates should have 3+ years of experience in data engineering, with a track record of building and managing cloud-based data systems.
Experience with real-time data processing frameworks and familiarity with containerization and microservices architecture is advantageous.

Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums are provided.
Competitive vacation, sick leave, and 20 paid holidays per year are included in the paid time off policy.
Flexible work schedules and telecommuting options promote work-life balance.
Opportunities for training, certification reimbursement, and career advancement programs support professional development.
Access to wellness programs, including gym memberships, health screenings, and mental health resources is available.
Life insurance and short-term/long-term disability coverage are part of the benefits package.
Confidential counseling and support services are offered through the Employee Assistance Program (EAP).
Financial assistance for continuing education and professional development is provided through tuition reimbursement.
Opportunities to participate in community service and volunteer activities are encouraged.
Employee recognition programs celebrate achievements and milestones.