What will you be doing?

• 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.

What do we need from you?

• 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.

What do you get in return?

• Love your career: Competitive total rewards package with excellent take home salaries, shifted work time bonus (if applicable) and an annual bonus plan!
• Love your development: Hone your skills or learn new ones with an annual training allowance; 2 paid professional development days, attend conferences, become certified, whatever you like!
• Love your work/life balance:  3 weeks of paid time off and flexible working hours. All you need is a stable internet connection!
• Love your workspace: We give you all the equipment you need to work from home including a laptop with your choice of OS, and budget to personalize your work environment!  
• Love your community: Blog during work hours; take a day off and volunteer for your favorite charity.

Pythian excels at helping businesses use their data and cloud to transform how they compete and win in this ever-changing environment by delivering advanced on-prem, hybrid, cloud and multi-cloud solutions to solve the toughest data challenges faster and better than anyone else. Founded and headquartered in Ottawa, Canada in 1997, Pythian now has more than 300 employees located around the globe with over 350 clients spanning industries from SaaS; media; gaming; financial services; e-commerce and more. Pythian is known for its technology-enabled data expertise covering everything from ETL to ML. We pride ourselves on our ability to deliver innovative solutions that meet the specific data goals of each client and have built meaningful partnerships with major cloud vendors AWS, Google and Microsoft. The powerful combination of our extensive expertise in data and cloud and our ability to keep on top of the latest bleeding edge technologies make us the perfect partner to help mid and large-sized businesses transform to stay ahead in today’s rapidly changing digital economy.