Senior Software Engineer- Data Engineering

We are seeking a talented and motivated Senior Data Engineer to join our dynamic Data Engineering team. As a key member of our engineering team, you will play a crucial role in constructing and optimizing data pipelines, implementing efficient storage solutions, and orchestrating the infrastructure necessary to support our customer’s data-driven initiatives. In addition, as a Senior Engineer you will be expected to lead engineering engagements by collaborating with cross-functional teams including customers, partners, and internal engineers.

• Location: Primarily Remote. Candidates must be based in CA or DC Metro Area for proximity to project and client teams.
• Security Clearance Requirement: Applicants must be US citizens and eligible to obtain and maintain an active Secret security clearance or above.

• Expert-level understanding and experience with SQL and relational database concepts
• Deep understanding of database technologies, data warehouses, and ETL tools (e.g., MySQL, PostgreSQL, Beam, Airflow, and Kafka). Proven track record of designing and implementing scalable data pipelines.
• Advanced experience with data analysis tools (eg., Jupyter, Colab, Pandas)
• Extensive experience with data visualization tools (eg., Tableau, Looker, PowerBI, Qlik, and SuperSet)
• Demonstrated experience developing comprehensive data strategies and facilitating data migrations into production systems.
• Expertise with cloud platforms (e.g., AWS, Azure, GCP).
• Proficiency in programming languages such as Python, Java, or C++.
• Strong software engineering skills with an emphasis on writing clean, modular, and maintainable code.
• Experience with version control systems (e.g., Git) and collaborative development workflows.
• Exceptional problem-solving and critical-thinking skills.
• Effective communication skills and ability to work in a collaborative team environment.

• Bachelor's or advanced degree in Computer Science, Data Science, Machine Learning, or a related field.
• Experience with other database technologies (eg., NoSQL, Graph)
• Any of the below cloud certifications:
• Google Cloud Professional Cloud Architect
• Google Cloud Professional Database Engineer certification
• Google Cloud Professional Data Engineer
• Experience with additional data processing tools and technologies (e.g., Spark, Hadoop).
• Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes).

Salary Range: $142,550 - $192,900

• Acquire, clean, and preprocess diverse datasets from various sources, establishing best practices and ensuring data quality standards.
• Design and build required infrastructure for optimal extraction, transformation and loading of data from various data sources using CSP managed services and SQL technologies, focusing on scalability and cost efficiency.
• Develop, maintain, and optimize mission-critical data pipelines to ensure a continuous flow of high-quality data, implementing robust monitoring and alerting.

• Architect and develop data migration strategies and schemas to lead complex customer migrations from on-prem to cloud technologies
• Oversee and execute high-volume data migration activities, ensuring data integrity and minimal downtime.
• Optimize databases and data warehouses for efficient querying and data storage, implementing advanced partitioning, indexing, and tuning techniques.

• Perform exploratory data analysis to uncover patterns, trends, and insights, providing actionable recommendations to technical and business stakeholders.
• Create visualizations and reports to communicate findings effectively to stakeholders both internally and externally, driving data-driven decision making.

• Collaborate with cross-functional teams, including software engineers, domain experts, and business analysts, to understand requirements and deliver integrated solutions, end-to-end data solutions.
• Create and maintain comprehensive documentation for data architectures, code, algorithms, and models. Ensure that the knowledge is shared and accessible within the team.

• Act on client feedback constructively to improve services and outcome, serving as a key technical contact for data-related discussions.
• Continuously seek ways to enhance the overall customer experience, proactively identifying and addressing complex data challenges.

• Stay updated on the latest developments in cloud data services,machine learning, data science, and analytics.
• Drive innovation by evaluating, proposing, and implementing cutting-edge techniques and technologies to address client challenges.

The Data Engineering & AI/ML capability serves as the backbone of our organization's data-driven operations. Comprising skilled professionals with expertise in data engineering, database management, and infrastructure architecture, our team is dedicated to designing and maintaining robust systems that ensure the seamless flow and accessibility of data. We specialize in constructing and optimizing data pipelines, implementing efficient storage solutions, and orchestrating the infrastructure necessary to support the company's data-driven initiatives.

Our focus extends beyond data management, encompassing the development of scalable and reliable systems that empower organizations to extract valuable insights, make informed decisions, and drive innovation.