Full-Time

Cloud Consultant

Data & Analytics

Updated on 11/8/2024

Pythian

Pythian

501-1,000 employees

Cloud migration and data management services

Data & Analytics
Enterprise Software
AI & Machine Learning

Mid

Remote in Canada

Category
Data Management
Data Analysis
Data Engineering
Data & Analytics
Required Skills
Talend
Python
Airflow
Data Science
Apache Spark
SQL
Java
Go
Scala
Jenkins
Terraform
LangChain
Google Cloud Platform
Requirements
  • Proficiency in a programming language such as Python, Java, Go or Scala
  • Experience with big data cloud technologies like EMR, Athena, Glue, Big Query, Dataproc, Dataflow.
  • Ideally you will have specific strong hands on experience working with Google Cloud Platform data technologies - Google BigQuery, Google DataFlow, and Executing PySpark and SparkSQL code at Dataproc
  • Understand the fundamentals of Spark (PySpark or SparkSQL) including using the Dataframe Application Programming Interface as well as analyzing and performance tuning Spark queries
  • Have experience developing and supporting robust, automated and reliable data pipelines
  • Develop frameworks and solutions that enable us to acquire, process, monitor and extract value from large dataset
  • Have strong SQL skills
  • Bring a good knowledge of popular database and data warehouse technologies & concepts from Google, Amazon or Microsoft (Cloud & Conventional RDBMS), such as BigQuery, Redshift, Microsoft Azure SQL Data Warehouse, Snowflake etc.
  • Have strong knowledge of a Data Orchestration solutions like Airflow, Oozie, Luigi or Talend
  • Have strong knowledge of DBT (Data Build Tool) or DataForm
  • Experience with Apache Iceberg, Hudi and Query engines like Presto (Trino) is a plus.
  • Knowledge of Data Catalogs (AWS Glue, Google DataPlex etc.), Data Governance and Data Quality Solutions (for eg. Great Expectations) is an added advantage.
  • Have knowledge of how to design distributed systems and the trade-offs involved
  • Experience with working with software engineering best practices for development, including source control systems, automated deployment pipelines like Jenkins and devops tools like Terraform
  • Experience in data modeling, data design and persistence (e.g. warehousing, data marts, data lakes).
  • Experience in performing DevOps activities such as IaC using Terraform, provisioning infrastructure in GCP/aws/Azure, defining Data Security layers etc.
  • Good to have knowledge of GenAI tools and frameworks such as Vertex AI, Langchain. Proficiency in prompt engineering.
Responsibilities
  • Design and development of end to end Cloud based solutions with heavy focus on application and data and good understanding of infrastructure.
  • Translate complex functional and technical requirements into detailed designs.
  • Write high-performance, reliable and maintainable code.
  • Develop test automation and associated tooling needed for the project.
  • Work on complex and varied Cloud based projects including tasks such as collecting, parsing, managing, analyzing, and visualizing very large datasets etc.
  • Maintain and execute DataOps tasks such as performance optimization of ETL/ELT pipeline, diagnosis and troubleshooting of pipeline issues, interpreting Data Observability Dashboards, Enhancements etc.
  • Perform Data Pipeline specific DevOps activities such as Infrastructure provisioning, writing IaC code, implementing data security etc.
  • Analyze potential issues and complete root cause analysis and assign issues to be resolved.
  • Follow up with Data Engineering team members to see fixes through completion.
  • Review bug descriptions, functional requirements and design documents, incorporating this information into test plans and test cases.
  • Performance tuning for batch and real-time data processing.
  • Secure components of clients’ Cloud Data platforms.
  • Health-checks and configuration reviews.
  • Data pipelines development – ingestion, transformation, cleansing.
  • Data flow integration with external systems.
  • Integration with data access tools and products.
  • Foundational CI/CD for all infrastructure components, data pipelines, and custom data apps.
  • Common operational visibility of the data platform from data platform infrastructure to data pipelines, machine learning apps.
  • Assist client application developers and advise on efficient data access and manipulations.
  • Define and implement efficient operational processes.

Pythian assists businesses in managing and optimizing their data and IT infrastructure through services like cloud migration, managed services, and advanced analytics. They help companies move data and applications to cloud platforms such as Google Cloud, AWS, and Microsoft Azure, while providing ongoing support for smooth operations. Pythian stands out by offering specialized services in machine learning and data science, enabling businesses to turn data into valuable insights. Their goal is to empower organizations to leverage cloud computing and advanced analytics to improve operations and drive growth.

Company Stage

Seed

Total Funding

$20.4M

Headquarters

Ottawa, Canada

Founded

1997

Growth & Insights
Headcount

6 month growth

0%

1 year growth

-5%

2 year growth

-1%
Simplify Jobs

Simplify's Take

What believers are saying

  • Pythian's recognition in DBTA's 'The Companies That Matter Most in Data' for six consecutive years underscores its industry leadership and reliability.
  • The launch of the EDP QuickStart offering allows businesses to see meaningful results quickly, enhancing client satisfaction and retention.
  • Strategic hires like Christina O'Reilly and Joey Jablonski bring valuable expertise and leadership, driving innovation and growth within the company.

What critics are saying

  • The competitive IT services market requires Pythian to continuously innovate to maintain its edge.
  • Integration challenges from acquisitions like Ensono and ManageServe could lead to operational inefficiencies.

What makes Pythian unique

  • Pythian's focus on cloud migration, managed services, and advanced analytics sets it apart from competitors who may not offer such a comprehensive suite of services.
  • Their Enterprise Data Platform (EDP) QuickStart offering provides a streamlined solution for companies to quickly demonstrate the value of data integration, a unique selling point in the market.
  • Pythian's specialized services in machine learning, AI, and data science enable businesses to turn data into actionable insights, differentiating them from traditional IT service providers.

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