Senior Python Engineer - ML and Data Science
ClickhouseSalary not specified
Full Time
Senior (5 to 8 years), Expert & Leadership (9+ years)
Not SpecifiedCompensation
Junior (1 to 2 years)Experience Level
Full TimeJob Type
UnknownVisa
Data & AnalyticsIndustries
Requirements
Candidates must possess 5+ years of professional software development experience with Python, a strong understanding of software engineering best practices, experience building and optimizing ETL/ELT processes and data pipelines, proficiency with SQL and database concepts, experience with data processing frameworks such as Pandas, an understanding of software design patterns and architectural principles, the ability to write clean, well-documented, and maintainable code, experience with unit testing and test automation, experience working with any cloud provider (GCP is preferred), experience with CI/CD pipelines and Infrastructure as code, experience with Containerization technologies like Docker or Kubernetes, and a Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience).
Responsibilities
The Data Engineer will develop and maintain data pipelines and ETL/ELT processes using Python, design and implement scalable, high-performance applications, work collaboratively with cross-functional teams to define requirements and deliver solutions, develop and manage near real-time data streaming solutions using Pub/Sub or Beam, contribute to code reviews, architecture discussions, and continuous improvement initiatives, monitor and troubleshoot production systems to ensure reliability and performance, and write clean, well-documented, and maintainable code.
Skills
Python
ETL/ELT
Data pipelines
SQL
Data processing frameworks
Pandas
Cloud computing (GCP preferred)
CI/CD pipelines
Docker
Kubernetes
Software engineering best practices
Version control
Testing and test automation
Architectural principles
Containerization
ShyftLabs
Data-driven decision-making solutions for organizations
About ShyftLabs
ShyftLabs helps organizations adopt a data-first approach to their decision-making processes. Their services focus on establishing systems that enable companies to make quicker and more informed decisions based on data analysis. This approach allows businesses to gain insights that can keep them ahead of their competitors. Unlike other companies that may offer generic consulting services, ShyftLabs emphasizes the importance of data in driving decisions, ensuring that organizations can leverage their data effectively to enhance their strategic planning and operational efficiency.
None, CanadaHeadquarters
2018Year Founded
VENTURE_UNKNOWNCompany Stage
Data & Analytics, ConsultingIndustries
11-50Employees
Benefits
Health Insurance
Hybrid Work Options
Professional Development Budget
Risks
Increased competition from startups offering innovative, cost-effective solutions.
Growing demand for in-house analytics teams reducing reliance on consultants.
Rapid AI advancements may outpace ShyftLabs' current technology offerings.
Differentiation
ShyftLabs specializes in data governance, warehousing, and predictive analysis services.
The firm empowers organizations with a data-first approach for decision-making.
ShyftLabs establishes processes for faster, insightful decisions to outpace competition.
Upsides
Increased demand for data governance due to stricter privacy regulations.
Growing interest in predictive analytics in retail for inventory optimization.
Rising adoption of cloud-based BI tools among SMEs for cost-effectiveness.
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