Manager Data Engineer

1 Month ago • 7 Years +

Job Summary

Job Description

As Manager Data Engineer, you will lead the data strategy, own the vision and roadmap for data products, and collaborate with various teams to execute data ingestion, integration, and transformation. Responsibilities include building monitoring processes, ensuring data quality, designing pipelines, and managing a team. You'll work with stakeholders to ensure data-related business requirements are met, ensuring the safe storage and transmission of data in line with privacy and compliance laws. The role requires strong problem-solving, communication, and leadership skills.
Must have:
  • 7+ years of experience in data management and warehousing.
  • 3+ years of experience in a Lead role managing engineers.
  • 5+ years of Experience in SQL and Snowflake.
  • 3+ years experience on Python.
Good to have:
  • Experience in retail domain.
  • Experience managing big data technology stack and restful APIs.
  • Good hands-on experience in Airflow and DBT.
  • Good hands on experience in ETL/ELT.
  • Experience with AWS Tools and Technologies (Redshift, S3, EC2, Glue).
  • Expertise with Data modeling skills, Advanced SQL with Oracle, MySQL, and Columnar Databases.
  • Technical knowledge in BI tools such as MicroStrategy, Looker.
Perks:
  • Competitive salary.
  • Strong insurance package.
  • Extensive learning and development resources.

Job Details

Position Overview:
We are looking for an experienced Manager Data Engineer to join our dynamic team. This role focuses on managing, supporting delivery and strategic initiatives such as data ingestion, integration, transformation, reporting and analytics. Broadly, it will work with every functional area of data engineering, data science teams & multiple Business partners.
 
ShyftLabs is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation.

Job Responsibilities:

    • Lead the data strategy, and own the vision and roadmap of data products to enable decision making and self-service for business and analytics teams.
    • Solid experience in emerging and traditional data stack components such as: batch and real time data ingestion, ETL, ELT, orchestration tools, on-prem and cloud DW, Python, structured, semi and unstructured databases.
    • Collaborate closely with the Data Engineering and Product team to execute on the set roadmap of data ingestion, integration and data transformation.
    • Work cross-functionally with enterprise-wide stakeholders including (but not limited to) Analytics, Data Science, FP&A, Accounting, merchandising, pricing teams.
    • Build a continuous monitoring process and tools to track the data management, data quality, and execute cleaning activities.
    • Track the overall data transformation initiative and provide feedback or suggestions from a risk management perspective.
    • Design, provide training and mentor/coach other team members.
    • Work with stakeholders to ensure that data related business requirements for protecting sensitive data are clearly defined, communicated, and well understood and considered as part of operational prioritization and planning.
    • Ensure the safe storage and transmission of data in line with privacy and compliance laws, data regulations, and internal company policies.
    • An ideal candidate will possess strong problem solving and conceptual thinking abilities in addition to communication, interpersonal and leadership skills.

Basic Qualifications:

    • Bachelor’s or Advanced degree in Information Systems, Information Management, Engineering, or related field. 
    • 7+ years of experience in data management, data warehousing and handling data engineering.
    • 3+ years of experience in Lead role managing set of engineers including hiring and performance evaluations.
    • 5+ years of Experience in SQL and Snowflake.
    • 3+ years experience on Python.
    • 2+ years of experience in retail domain.
    • 3+ years managing big data technology stack and restful APIs.
    • Good hands-on experience in Airflow and DBT.
    • Good hands on experience in ETL/ELT.
    • Experience with AWS Tools and Technologies (Redshift, S3, EC2, Glue).
    • Expertise with Data modeling skills, Advanced SQL with Oracle, MySQL, and Columnar Databases.
    • Strong knowledge of designing data pipelines and understanding details around orchestration, integration, data transformations.
    • Excellent communication skills, both verbal and written, and the ability to build trust-based relationships with business partners.
    • Technical knowledge in BI tools such as MicroStrategy, Looker.
    • Proven record of handling, managing, collaborating and delivering data products on time and meeting quality standards.
We are proud to offer a competitive salary alongside a strong insurance package. We pride ourselves on the growth of our employees, offering extensive learning and development resources. 

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