Description:

The Cloud Data Engineer (The Data Pipeline Architect) will design, develop, and manage cloud-based data infrastructures that support analytical and operational needs across the organization.
This role involves collaborating with data scientists, analysts, and software engineers to build secure, efficient, and scalable data pipelines and storage solutions.
Key responsibilities include creating and managing scalable data pipelines that support ETL processes, developing and maintaining cloud-based data storage solutions, and optimizing data structures for performance and reliability.
The engineer will work closely with cross-functional teams to understand data requirements and implement solutions that support analytics and machine learning models.
Ensuring data security and compliance with industry standards is crucial, including managing data access controls and audit logs.
The role also involves improving the performance of data processing workflows, developing automation scripts and tools, and monitoring and troubleshooting data pipelines to maintain smooth data flow.

Requirements:

Strong experience with cloud data platforms (AWS, GCP, Azure) and data processing tools like Apache Spark, Apache Beam, or AWS Glue is required.
Proficiency in programming languages such as Python, Java, or Scala for data manipulation and pipeline automation is essential.
Experience in developing and managing complex ETL workflows that handle large data volumes is necessary.
Familiarity with implementing data security measures and ensuring compliance with industry standards is required.
Strong collaboration and problem-solving skills are needed to work with cross-functional teams and troubleshoot data-related issues.
A Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field is required, with equivalent experience considered.
Certifications such as Google Professional Data Engineer, AWS Certified Big Data – Specialty, or Microsoft Certified: Azure Data Engineer Associate are highly desirable.
A minimum of 5+ years of experience in data engineering, with at least 3+ years focusing on cloud-based data solutions, is required.
Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow, Dataflow, Step Functions) is necessary.
Familiarity with database technologies such as SQL, NoSQL, and data warehousing solutions (e.g., BigQuery, Redshift, Snowflake) is required.

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.
Flexible work schedules and telecommuting options promote work-life balance.
Opportunities for training, certification reimbursement, and career advancement programs are available for professional development.
Access to wellness programs, including gym memberships, health screenings, and mental health resources, is offered.
Life insurance and short-term/long-term disability coverage are provided.
Confidential counseling and support services for personal and professional challenges are available through the Employee Assistance Program (EAP).
Financial assistance for continuing education and professional development is offered through tuition reimbursement.
Opportunities to participate in community service and volunteer activities are available for community engagement.
Employee recognition programs celebrate achievements and milestones.