Senior Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• The Senior Data Engineer acts as a seasoned individual contributor within a team, with the expectation of ongoing development in leadership, technical mentorship, and guidance skills.

• With minimal supervision from leadership, you will architect, construct, and enhance scalable data solutions that address business and customer requirements while ensuring that projects adhere to scope, timelines, and delivery obligations.

• Contribute to the long-term data strategy of the program, influence architectural decisions, and work closely with software engineers, product managers, analysts, architects, and stakeholders to create reliable, secure, and scalable data platforms.

• Act as the primary data engineering lead for projects, utilizing robust leadership and communication skills to drive enhancements in data engineering processes, platform reliability, and best practices in engineering.

• Assess and recommend various technical strategies to tackle complex data engineering and architectural challenges.

• Design, develop, maintain, and optimize scalable data pipelines that support both batch and real-time processing.

• Create and implement resilient ETL/ELT workflows that convert raw data into reliable, usable datasets.

• Construct and sustain scalable data models, data warehouses, and cloud-native data architectures.

• Provide data architecture recommendations and successfully execute approved solutions.

• Ensure data quality, integrity, governance, lineage, security, and observability across data platforms.

• Enhance database performance, query execution, storage strategies, and overall system scalability.

• Diagnose and resolve production issues while implementing long-term improvements to boost system reliability and performance.

• Collaborate with cross-functional teams to translate business requirements into scalable technical solutions.

• Present technical designs, architecture diagrams, and implementation strategies to clients, stakeholders, partners, and engineering teams.

• Advocate for best practices in data engineering, coding standards, automation, and operational excellence.

• Mentor junior engineers through providing technical guidance, conducting code reviews, facilitating design discussions, and sharing knowledge.

• Lead small projects or serve as the technical lead for data engineering initiatives as necessary.

• Communicate technical challenges, risks, and progress effectively with engineering teams, leadership, clients, and stakeholders.

• Participate in technical interviews and contribute to hiring decisions.

⛳️ Requirements

• A Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related technical field with over 7 years of professional experience.

• More than 7 years of experience in designing, building, and maintaining enterprise-scale data platforms and pipelines.

• Strong expertise in SQL, with experience in developing, optimizing, and troubleshooting complex queries and large datasets.

• Professional experience in developing software and data solutions using Python, Java, Scala, or a similar programming language.

• Experience in designing, developing, and maintaining ETL/ELT pipelines for batch and real-time data processing.

• Familiarity with cloud-based data platforms and services in AWS, Microsoft Azure, or Google Cloud Platform.

• Experience with modern cloud data platforms such as Snowflake, Databricks, Amazon Redshift, Google BigQuery, or Azure Synapse Analytics.

• Proficiency with relational database technologies such as PostgreSQL, SQL Server, Oracle, or MySQL, along with knowledge of NoSQL database solutions.

• Experience with distributed data processing frameworks like Apache Spark or equivalent big data technologies.

• Strong grasp of data modeling, dimensional modeling, schema design, data warehousing, and database optimization.

• Knowledge of implementing data quality, validation, governance, metadata management, and data lineage best practices.

• Experience handling structured, semi-structured, and unstructured data from various sources.

• Familiarity with version control systems like Git and CI/CD practices that support data engineering workflows.

• Understanding of data security, privacy, encryption, and access control principles.

• Experience in monitoring, troubleshooting, and optimizing production data systems for scalability, availability, and performance.

• Background working within Agile software development environments and collaborating with cross-functional engineering teams.

• Strong analytical, troubleshooting, and problem-solving abilities with the capacity to make informed technical decisions.

• Excellent written and verbal communication skills, capable of explaining technical concepts to both technical and non-technical audiences.

• Proven ability to mentor junior engineers through code reviews, technical guidance, and knowledge sharing.

• Ability to obtain and maintain a U.S. Public Trust clearance.

🏝️ Benefits

• Company-subsidized health, dental, and vision insurance.

• Flexible PTO.

• 401K with employer match.

• Paid parental leave after one year of service.

• Employee Assistance Program.