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Senior Data Engineer

Senior Data Engineer

Friday, September 27, 2024

Direct Hire

Remote, USA, United States

As a Senior Data Engineer at , you will be at the forefront of transforming our data strategy, driving the design and execution of cutting-edge data architectures that are vital to our company’s growth and innovation. This role demands a blend of deep technical expertise, strategic vision, and leadership, as you will be responsible for architecting and optimizing sophisticated data solutions that cater to both operational efficiency and advanced analytics. You will collaborate closely with cross-functional teams, including data scientists, product managers, and business stakeholders, to ensure that our data systems are robust, scalable, and aligned with the company’s strategic objectives.

In this role, you will lead the development and enhancement of comprehensive data pipelines and architectures and major cloud platforms like AWS or Azure. Your experience in managing large-scale data ecosystems and streamlining data workflows will be instrumental in advancing our data capabilities and generating valuable business insights. Additionally, you will mentor and guide junior data engineers, champion best practices, and play a key role in shaping and executing our data strategy to maximize the impact and utilization of our data assets.

Responsibilities

  • Lead the design, development, and optimization of scalable data pipelines and architectures, ensuring efficient data processing, integration, and accessibility across diverse systems and platforms.
  • Architect and implement robust ETL (Extract, Transform, Load) processes using advanced technologies.
  • Develop and oversee data storage solutions, including relational databases (e.g., Oracle, Sqlserver) and NoSQL databases (e.g., Dynamo DB), ensuring high performance, data integrity, and scalability.
  • Design data warehouse solutions using dimensional modeling techniques and model NoSQL databases such as DynamoDB to optimize data management.
  • Collaborate with data scientists, analysts, and business stakeholders to define data requirements, design data models, and create solutions that facilitate actionable insights and strategic decision-making.
  • Provide technical leadership and mentorship to data engineering teams, advocating for best practices in data engineering, data quality, and data management to foster a culture of excellence.
  • Drive the implementation and maintenance of data security and governance practices, ensuring adherence to industry standards and regulations, and protecting sensitive information from unauthorized access.
  • Conduct comprehensive code reviews and performance tuning, ensuring the delivery of efficient, high-quality, and maintainable data solutions that meet organizational needs.
  • Stay abreast of emerging technologies and industry trends, evaluating and integrating new tools and methodologies to continuously enhance the company’s data infrastructure and capabilities.
  • Manage complex data engineering projects, overseeing project planning, risk management, and stakeholder communication to ensure timely and successful delivery of data solutions.
  • Contribute to the refinement of data engineering practices and processes, implementing improvements to boost team efficiency, data quality, and alignment with the overall data strategy.
  • Collaborate with cross-functional teams to address and resolve intricate data-related issues, ensuring consistent and accurate data delivery that supports all business requirements.
  • Develop and maintain a comprehensive data strategy and roadmap that aligns with the company's overall business objectives and technological landscape.
  • Design and implement data governance frameworks and policies to ensure data consistency, accuracy, and compliance across all business units.
  • Oversee the evaluation and selection of data technologies and tools, making strategic recommendations to optimize data architecture and support evolving business needs.
  • Lead initiatives to modernize data architecture, including the transition to cloud-based data solutions and the adoption of data mesh or data fabric principles to improve data accessibility and usability.
  • Facilitate cross-departmental workshops and meetings to ensure alignment on data architecture decisions, foster collaboration, and drive data-driven culture within the organization.
  • Migrate data from RDBMS to NoSQL databases like DynamoDB.
  • Adhere to company policies and procedures, upholding high standards for data quality, integrity, and security, while contributing to the protection and reputation of the company’s data assets.
  • Actively represent and embody the company culture, fostering an environment of teamwork, transparency, and accountability in all professional interactions and initiatives.
  • Readily facilitates position with observation of flexible hours as needed to meet or exceed department needs, and complete other tasks as assigned.

Desired Qualifications

  • Demonstrated experience in designing and deploying scalable data architectures, with a strong focus on ETL processes, data warehousing, and real-time data processing solutions.
  • Extensive expertise with big data technologies such as Kinesis, databricks, redshift, AWS Glue as well as proficiency in relational databases (e.g.,Oracle and sqlserver) and NoSQL databases (e.g.,Dynamo DB).
  • Advanced analytical skills with a proven ability in relational data modeling, dimensional modeling, integration, and quality management, including a track record of addressing complex data challenges and optimizing data pipelines.
  • Exceptional leadership and mentoring skills, evidenced by a history of guiding data engineering teams, implementing best practices, and cultivating a culture of technical excellence and continuous improvement.
  • Excellent communication abilities, both verbal and written, with a knack for translating intricate data concepts and technical details into clear, actionable insights for diverse audiences.
  • Proficiency in enforcing data security and governance practices, including expertise in encryption techniques, access controls, and ensuring compliance with industry regulations to maintain data integrity and protection.

Desired Education and Experience

  • Bachelor's or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
  • Minimum of 8-10 years of experience in data engineering, with a proven track record of designing and implementing large-scale data architectures and ETL processes.
  • At least 5 years of hands-on experience with big data technologies such as DataBricks, AWS Glue, Dimensional modeling, NoSQL table design.
  • Demonstrated expertise in relational databases (e.g., Oracle, SQLServer) and NoSQL databases (e.g., Dynamo DB), including experience in performance tuning and optimization.
  • Experience leading and mentoring teams of data engineers, with a history of driving technical excellence and promoting best practices in data management.
  • Proven experience with cloud platforms such as AWS, Azure, or Google Cloud, including familiarity with cloud- based data storage and processing services.
  • Strong analytical skills with a minimum of 5 years working on complex data modeling, data integration, and data quality projects.
  • Certifications related to data engineering or cloud

Compensation and Other
Highly competitive compensation package, including attractive benefits. 
Target base salary is $165,000

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