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Data Engineer

Remote: 
Full Remote
Contract: 
Experience: 
Expert & Leadership (>10 years)
Work from: 
California (USA), United States

Offer summary

Qualifications:

10+ years of data solutions experience, Bachelor's or Master's in related field, Extensive hands-on data system design, Experience with modern data pipelines.

Key responsabilities:

  • Lead a team of data engineers
  • Design and maintain scalable data pipelines
  • Provide technical guidance and mentorship
  • Collaborate with stakeholders on data needs
LanceSoft, Inc. logo
LanceSoft, Inc. XLarge https://www.lancesoft.com/
1001 - 5000 Employees
See more LanceSoft, Inc. offers

Job description

Title: Senior Software Engineer/Data Engineer
Location: Remote
Duration: 6 Months (Temp to perm)

Description:

About the role:
  • As the Senior Software Engineer, you will lead a team of data engineers in designing, building, and maintaining high-performance software system to manage analytical data pipelines that fuel the organization’s data strategy using software engineering best practices. Beyond technical expertise, you will also serve as a change leader, guiding teams through adopting new tools, technologies, and workflows to improve data management and processing.
  • This position requires extensive hands-on data system design and coding experience, as well as the development of modern data pipelines (AWS Step functions, Prefect, Airflow, Luigi, Python, Spark, SQL) and associated code in AWS.
  • You will work closely with stakeholders across the business to understand their data needs, ensure scalability, and foster a culture of innovation and learning within the data engineering team and beyond.

Key Responsibilities:
· Be responsible for the overall architecture of a specific module within a product (e.g., Data-ingestion, near-real-time-data-processor, etc.), perform design and assist implementation considering system characteristics to produce optimal performance, reliability and maintainability.
· Provide technical guidance to team members, ensuring they are working towards the product's architectural goals.
· Create and manage RFCs (Request for Comments) and ADRs (Architecture Decision Records), Design notes and technical documentation for your module, following the architecture governance processes.
· Lead a team of data engineers, providing mentorship, setting priorities, and ensuring alignment with business goals.
· Architect, design, and build scalable data pipelines for processing large volumes of structured and unstructured data from various sources.
· Collaborate with software engineers, architects, and product teams to design and implement systems that enable real-time and batch data processing at scale.
· Be the go-to person for PySpark-based solutions, ensuring optimal performance and reliability for distributed data processing.
· Ensure that data engineering systems adhere to the best data security, privacy, and governance practices in line with industry standards.
· Perform code reviews for the product, ensuring adherence to company coding standards and best practices.
· Develop and implement monitoring and alerting systems to ensure timely detection and resolution of data pipeline failures and performance bottlenecks.
· Act as a champion for new technologies, helping ease transitions and addressing concerns or resistance from team members.

Ideal Candidate:
· Experience leading a data engineering team with a strong focus on software engineering principles such as KISS, DRY, YAGNI etc.
· Candidate MUST have experience in owning large, complex system architecture and hands-on experience designing and implementing data pipelines across large-scale systems.
· Experience implementing and optimizing data pipelines with AWS is a must.
· Production delivery experience in Cloud-based PaaS Big Data related technologies (EMR, Snowflake, Data bricks etc.)
· Experienced in multiple Cloud PaaS persistence technologies, and in-depth knowledge of cloud- based ETL offerings and orchestration technologies (AWS Step Function, Airflow etc.)
· Experienced in stream-based and batch processing, applying modern technologies
· Working experience with distributed file systems (S3, HDFC, ADLS), table formats (HUDI, Iceberg), and various open file formats (JSON, Parquet, Csv, etc.)
· Strong programming experience in PySpark, SQL, Python, etc.
· Database design skills including normalization/de-normalization and data warehouse design
· Knowledge and understanding of relevant legal and regulatory requirements, such as SOX, PCI, HIPAA, Data Protection
· Experience in the healthcare industry, a plus
· A collaborative and informative mentality is a must!

Toolset:
· AWS, preferably AWS certified Data Engineer and AWS certified Solutions Architect.
· Proficiency in at least one programming language C#, GoLang, JavaScript or ReactJs
· Spark / Python / SQL
· Snowflake/ Databricks / Synapse / MS SQL Server
· ETL / Orchestration Tools (Step Function, DBT etc.)
· ML / Notebooks

Education and experience required
· Bachelors or Master’s in Computer Science, Information Systems, or an engineering field or relevant experience.
· 10+ years of related experience in developing data solutions and data movement.

Required profile

Experience

Level of experience: Expert & Leadership (>10 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Collaboration
  • Mentorship

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