Senior Data Engineer

🕒 il y a 12 jours

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Ad Hoc LLC

Site WebLinkedInTous les Emplois

501 - 1000 employés

Fondée en 2014

💼 Conseil

🏥 Santé

📦 Logistique

Consulting • Healthcare • Logistics

Ad Hoc LLC est une entreprise de conseil en technologie qui modernise les services numériques gouvernementaux grâce à la conception centrée sur l'humain, au développement de plateformes et de mobiles et à la transformation des systèmes. L'entreprise est spécialisée dans l'interopérabilité des données, l'infrastructure API, les pratiques DevOps et cybersécurité, ainsi que dans l'automatisation par IA visant à aider les agences fédérales, étatiques et locales à étendre leurs services, réduire leurs coûts et améliorer l'expérience utilisateur. Parmi ses travaux notables figurent le traitement à grande échelle de l'inscription à Medicare, l'application mobile VA Health and Benefits, et l'accès à des milliards de réclamations de santé via des APIs modernes.

Description

• Senior Data Engineer serves as an experienced individual contributor within a team, with the expectation that you will continue to develop your leadership, technical guidance, and mentoring skills. • With minimal oversight from leadership, you will design, build, and optimize scalable data solutions that support business and customer needs while ensuring projects meet scope, schedule, and delivery commitments. • Contribute to the long-term data strategy of the program, influence architectural decisions, and collaborate closely with software engineers, product managers, analysts, architects, and stakeholders to deliver reliable, secure, and scalable data platforms. • Serve as the primary data engineering lead for initiatives and utilize strong leadership and communication skills to drive improvements in data engineering processes, platform reliability, and engineering best practices. • Evaluate and recommend multiple technical approaches to solve complex data engineering and architecture challenges. • Design, develop, maintain, and optimize scalable data pipelines supporting both batch and real-time processing. • Design and implement robust ETL/ELT workflows that transform raw data into reliable, consumable datasets. • Build and maintain scalable data models, data warehouses, and cloud-native data architectures. • Generate data architecture recommendations and successfully implement approved solutions. • Ensure data quality, integrity, governance, lineage, security, and observability across data platforms. • Optimize database performance, query execution, storage strategies, and overall system scalability. • Diagnose and resolve production issues while implementing long-term improvements to increase 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. • Champion data engineering best practices, coding standards, automation, and operational excellence. • Mentor junior engineers through technical guidance, code reviews, design discussions, and knowledge sharing. • Lead small projects or serve as the technical lead for data engineering initiatives when needed. • Effectively communicate technical challenges, risks, and progress with engineering teams, leadership, clients, and stakeholders. • Participate in technical interviews and contribute to hiring decisions.

🎯 Exigences

• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related technical discipline with 7+ years of professional experience. • 7+ years of experience designing, building, and maintaining enterprise-scale data platforms and data pipelines. • Strong proficiency in SQL with experience developing, optimizing, and troubleshooting complex queries and large datasets. • Professional experience developing software and data solutions using Python, Java, Scala, or a comparable programming language. • Experience designing, developing, and maintaining ETL/ELT pipelines for batch and real-time data processing. • Experience working with cloud-based data platforms and services within 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. • Experience with relational database technologies such as PostgreSQL, SQL Server, Oracle, or MySQL, along with familiarity with NoSQL database solutions. • Experience with distributed data processing frameworks such as Apache Spark or equivalent big data technologies. • Strong understanding of data modeling, dimensional modeling, schema design, data warehousing, and database optimization. • Experience implementing data quality, validation, governance, metadata management, and data lineage best practices. • Experience working with structured, semi-structured, and unstructured data from multiple sources. • Experience with version control systems such as Git and CI/CD practices supporting data engineering workflows. • Understanding of data security, privacy, encryption, and access control principles. • Experience monitoring, troubleshooting, and optimizing production data systems for scalability, availability, and performance. • Experience working within Agile software development environments and collaborating across cross-functional engineering teams. • Strong analytical, troubleshooting, and problem-solving skills with the ability to make sound technical decisions. • Excellent written and verbal communication skills with the ability to explain technical concepts to both technical and non-technical audiences. • Demonstrated ability to mentor junior engineers through code reviews, technical guidance, and knowledge sharing. • Ability to obtain and maintain a U.S. Public Trust clearance.

🏖️ Avantages

• Company-subsidized health, dental, and vision insurance • Flexible PTO • 401K with employer match • Paid parental leave after one year of service • Employee Assistance Program