Sigmoid enables business transformation using data and analytics, leveraging real-time insights to make accurate and fast business decisions by building modern data architectures using cloud and open source. Some of the world’s largest data producers engage with Sigmoid to solve complex business problems. Sigmoid brings deep expertise in data engineering, predictive analytics, artificial intelligence, and Data Ops. Sigmoid has been recognized as one of the fastest-growing technology companies in North America in 2020, 2021 and 2022 by Financial Times, Inc. 5000, and Deloitte Technology Fast 500.

Having started in 2013 by three IIT Kharagpur Alumni, Rahul, Lokesh & Mayur. We have now grown into a 550+ members strong team with offices in San Francisco, Jersey City, Dallas, Peru, and Bangalore, India. Sigmoid is rapidly growing & is backed by Sequoia Capital.

Engineering Leader / Solutions Architect – Canada

Job Description:

- Align Sigmoid with key Client initiatives
- Interface daily with customers across leading Fortune 500 companies to understand strategic requirements
- Connect with CIO, VP and Director level clients on a regular basis.
- Ability to understand business requirements and tie them to technology solutions

- Build a delivery plan with domain experts and stay on track

- Design, develop and evolve highly scalable and fault-tolerant distributed components using Big data technologies.
- Excellent experience in Application development and support, integration development and data management.

- Build team and manage it day to day basis

- Play the key role of hiring manager to build the future of Sigmoid. Solutions Architect
- Guiding developers in day to day design and coding tasks, stepping in to code if needed.
- Define your team structure, Hire and train your team as needed

- Stay up-to-date on the latest technology to ensure the greatest ROI for customer & Sigmoid

- Hands on coder with positive understanding on enterprise level code
- Design and implement APIs,



abstractions and integration patterns to solve challenging distributed computing problems
- Experience in defining technical requirements, data extraction, data transformation, automating jobs, productionizing jobs, and exploring new big data technologies within a Parallel Processing environment
- Must be a strategic thinker with the ability to think unconventional / out of box
- Analytical and data driven orientation.
- Raw intellect, talent and energy are critical.
- Entrepreneurial and Agile : understands the demands of a private, high growth company.
- Ability to be both a leader and hands on “doer.”

- Facilitate in Technical Aspects

- Help Technical architects understand clients business constraints while drawing out architectures
- Build a business case around highly scalable and fault-tolerant distributed components designed by technical architects
- Lead integration effort onsite with the client technical teams
- Understand client acceptance criteria and emulate that for offshore technical teams
- Receive and monitor technical deliverables from the offshore team and present to client teams

Qualifications:

- 10-15 years track record of relevant work experience and a Computer Science or related technical discipline is required
- Dynamic leader who has directly managed team of highly competent developers in fast paced work environment
- Experience in Architecture and delivery of Enterprise scale applications.

Preferred Qualification:

- Experience in agile methodology Solutions Architect
- Development and support experience in Big Data domain
- Architecting, developing, implementing and maintaining Big Data solutions
- Experience with database modeling and development, data mining and warehousing.
- Experience with Hadoop ecosystem (HDFS, MapReduce, Oozie, Hive, Impala, Spark, Kerberos, KAFKA, etc)
- Technical knowledge in AWS/GCS Stack. Vertica, Snowflake, Druid a plus.
- Experience with tech stack involving S3, Lambda, Step Functions, sns, DynamoDb, AWS Glue, Airflow, Redshift, BigQuery

📌 Solutions Architect (Toronto)
🏢 Sigmoid
📍 Toronto