ShyftLabs

ShyftLabs

ShyftLabs is a strategic partner in driving digital transformation with tailored solutions for businesses. Specializing in end-to-end software solutions, they integrate seamlessly to accelerate value creation, particularly in the retail sector. Their e...

IT Services
51-250
Founded 2018

Description

  • Design, build, and maintain scalable batch and real-time ETL/ELT data pipelines using cloud services.
  • Architect and implement data infrastructure for high-volume data ingestion and processing.
  • Develop and manage the central data warehouse in Google BigQuery.
  • Design data models, schemas, and table structures optimized for performance and maintainability.
  • Write clean, efficient SQL and Python code to transform raw data into curated datasets.
  • Build transformation workflows that support analytics, reporting, and data science initiatives.
  • Monitor, troubleshoot, and optimize data infrastructure for performance, reliability, and cost efficiency.
  • Implement data quality checks, validation rules, monitoring, governance, observability, and lineage tracking.
  • Collaborate with engineers, analysts, and data scientists to deliver data products and infrastructure.
  • Lead client and stakeholder communication and align technical solutions with business strategy.

Requirements

  • 5+ years of hands-on experience in data engineering, data integration, or data platform development.
  • Degree in Computer Science, Engineering, Mathematics, or a related STEM discipline.
  • Strong programming and query skills in SQL and Python.
  • Experience with distributed version control systems such as Git in an Agile/Scrum environment.
  • Experience designing and orchestrating ETL pipelines, particularly with Databricks.
  • Experience working in cloud environments such as GCP, AWS, or Azure.
  • Experience with database systems such as MongoDB and Elasticsearch.
  • Strong understanding of data warehousing and dimensional modeling methodologies.
  • Hands-on experience with Airflow and Hadoop.
  • Experience using Docker for containerized workflows and reproducible environments.
  • Ability to identify opportunities to improve data quality, reliability, and automation.
  • Strong business awareness and communication skills with the ability to collaborate with technical teams and business stakeholders.
  • Experience within the retail industry is a plus.
  • Master’s degree in Computer Science, Engineering, or a related discipline is preferred.
  • Experience with enterprise-scale data platforms and Fortune 500 clients is preferred.
  • Familiarity with Druid and its Python API, including Kafka integrations, is preferred.
  • Strong experience using Apache Spark for large-scale data processing is preferred.
  • Experience designing real-time streaming data architectures is preferred.
  • Experience supporting AI/ML systems or agentic AI workflows is preferred.

Benefits

  • Fully remote work arrangement with the possibility of transitioning to a hybrid model in the future.
  • 100% employer-paid health, dental, and vision insurance premiums for employees and dependents.
  • Coverage available from day one.
  • Access to extensive learning and development resources.
  • Opportunity to work with Fortune 500 clients and influence strategy as the company scales.
  • Equal-opportunity, inclusive work environment with accommodation support during the interview process.

Interested in this position?

Apply directly on the company website

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