As a member of our Software Engineering Group, we look first and foremost for people passionate about solving business problems through innovation and engineering practices. You'll be required to apply your depth of knowledge and expertise to all aspects of the software development lifecycle and partner continuously with your many stakeholders daily to stay focused on common goals. We embrace a culture of experimentation and constantly strive for improvement and learning. You'll work in a collaborative, trusting, thought-provoking environment-one that encourages diversity of thought and creative solutions that are in the best interests of our customers globally. A successful candidate is an active listener with good interpersonal communication and can ask for and give feedback to others. The Sr. Data Engineer is someone who constantly communicates with different internal and external stakeholders and business owners.
Duties and responsibilities
Work with management and internal stakeholders to define business requirements and analytical needs and execute against them.
Develop a deep understanding of existing eCommerce performance, customer, brands, and productivity metrics, and develop new KPIs, metrics, and measures to gauge eCommerce performance.
Own regular and ad-hoc analysis on operational performance and projects to continuously improve and scale Alchemee's eCommerce operations.
Work to define and structure eCommerce customer and operational data and ensure the reliability and integrity of data sources.
Perform data modeling using/modifying existing models.
Build automated data flows on AWS by extracting and transforming data from existing e-commerce systems, log files, and API sources.
Qualifications
Expert-level skills in writing and optimizing SQL.
Experience operating very large data warehouses or data lakes.
Expertise in ETL optimization, designing, coding, and data ingestion from Rest and GraphQL API.
Experience with building data pipelines and applications to stream and process datasets at low latencies.
Show efficiency in handling data - tracking data lineage, ensuring data quality, and improving discoverability of data.
Sound knowledge of distributed systems and data architecture utilizing Lambda, Python, and Jupyter.
Experience in AWS Data Analytics platform and related services - S3, AWS Glue, Redshift, Athena, Lake Formation, Lambda, etc.
Experience in building data pipelines using Spark/Glue
Good understanding of Data Warehousing and Data Modelling concepts on AWS Redshift
Experience in designing and optimizing Redshift Workloads
Good knowledge of defining data access roles and permission for Redshift
Capable of learning and adapting to new technologies along with good Analytical skills
Experience working on Visualization tools like AWS QuickSight, Tableau, or Sigma is a plus.
Experience in Java, IntelliJ, Bitbucket, Gradle is plus.
4-year degree (Economics, Statistics, Mathematics, Computer Science, MIS, or similar focus) and 3-5 years of relevant work experience.
5+ years of experience in ETL, Data warehousing, Data pipelines, Data Analytics, in Microsoft or Amazon cloud. AWS Data Stack is preferred.As a member of our Software Engineering Group, we look first and foremost for people passionate about solving business problems through innovation and engineering practices. You'll be required to apply your depth of knowledge and expertise to all aspects of the software development lifecycle and partner continuously with your many stakeholders daily to stay focused on common goals. We embrace a culture of experimentation and constantly strive for improvement and learning. You'll work in a collaborative, trusting, thought-provoking environment-one that encourages diversity of thought and creative solutions that are in the best interests of our customers globally. A successful candidate is an active listener with good interpersonal communication and can ask for and give feedback to others. The Sr. Data Engineer is someone who constantly communicates with different internal and external stakeholders and business owners.
Duties and responsibilities
Work with management and internal stakeholders to define business requirements and analytical needs and execute against them.
Develop a deep understanding of existing eCommerce performance, customer, brands, and productivity metrics, and develop new KPIs, metrics, and measures to gauge eCommerce performance.
Own regular and ad-hoc analysis on operational performance and projects to continuously improve and scale Alchemee's eCommerce operations.
Work to define and structure eCommerce customer and operational data and ensure the reliability and integrity of data sources.
Perform data modeling using/modifying existing models.
Build automated data flows on AWS by extracting and transforming data from existing e-commerce systems, log files, and API sources.
Qualifications
Expert-level skills in writing and optimizing SQL.
Experience operating very large data warehouses or data lakes.
Expertise in ETL optimization, designing, coding, and data ingestion from Rest and GraphQL API.
Experience with building data pipelines and applications to stream and process datasets at low latencies.
Show efficiency in handling data - tracking data lineage, ensuring data quality, and improving discoverability of data.
Sound knowledge of distributed systems and data architecture utilizing Lambda, Python, and Jupyter.
Experience in AWS Data Analytics platform and related services - S3, AWS Glue, Redshift, Athena, Lake Formation, Lambda, etc.
Experience in building data pipelines using Spark/Glue
Good understanding of Data Warehousing and Data Modelling concepts on AWS Redshift
Experience in designing and optimizing Redshift Workloads
Good knowledge of defining data access roles and permission for Redshift
Capable of learning and adapting to new technologies along with good Analytical skills
Experience working on Visualization tools like AWS QuickSight, Tableau, or Sigma is a plus.
Experience in Java, IntelliJ, Bitbucket, Gradle is plus.
4-year degree (Economics, Statistics, Mathematics, Computer Science, MIS, or similar focus) and 3-5 years of relevant work experience.
5+ years of experience in ETL, Data warehousing, Data pipelines, Data Analytics, in Microsoft or Amazon cloud. AWS Data Stack is preferred.
