Sr. Data Engineer to designed and developed data pipelines for data ingestion using Spark and c[...]

4 weeks ago

Old Toronto, Canada S I Systems Full time
Sr. Data Engineer to designed and developed data pipelines for data ingestion using Spark and create workflows using Airflow for our large banking client - 34083

Sr. Data Engineer to designed and developed data pipelines for data ingestion using Spark and create workflows using Airflow for our large banking client - 34083

Location Address: Hybrid - Downtown Toronto – 1-2 days / week (Wednesdays and Thursdays) – need candidates in GTA

Contract Duration: ASAP to Oct 31, 2024 – approx. 4 months

Possibility of extension

Schedule Hours: 9am-5pm Monday-Friday; standard 37.5 hrs/week

Story Behind the Need

Business group: Enterprise Platform Architecture & Enablement – building data pipelines from end to end

Project: Initiative working with an external vendor (fraud and know your customer technology) – ensuring data is properly ingested, structured; work in coordinating with fraud, digital teams and business partners to ensure data is effectively shaped – stage: through proof of concept, current coordination with vendor partners and ensuring their technologies align to ours, early stages and ramping up

Typical Day in Role:

Collaborate with business lines and other stakeholders and identify opportunities to drive business value by leveraging data engineer.

Efficiently handle large volumes of structured and unstructured data through ingestion, modeling, transformation, and storage across diverse data stores. Leverage distributed computing tools (e.g., Spark, Cloud) for analysis, data mining, and modeling

Collaborate with operation, and other analytics teams to deploy models and automate pipelines / workflows in production across different channels and platforms

Work with the team to design the project architecture and road map.

Create and apply model and algorithm testing strategies to measure the effectiveness of models and make ongoing changes.

Prepare detailed documentation to outline data sources, models, and algorithms used and developed.

Present results to business line stakeholders and help implement real world data-driven changes.

Candidate Requirements/Must Have Skills:

  • 10+ years of progressive experience as Data Engineer.
  • 5+ years’ experience with SQL/NOSQL and relational databases technologies/concepts for both querying/manipulating datasets and managing /controlling databases.
  • 3+ years’ experience with Google Cloud Platform about Data Ingesting and on-prem to cloud environment data replication.
  • 5+ years’ combined experience programming in Python or equivalent languages (Scala, Java), and tools such as Spark, Airflow (please list which)

Nice-To-Have Skills:

  • Experience with DBT (Data Building Tool)
  • Experience in creating Docker images
  • Experience / knowledge of MongoDB
  • Experience from banking / financial services

Education:

Bachelor’s Degree or equivalent in in Computer Science, Engineering, or relevant field.

Best VS. Average Candidate:

GCP, Python and Spark experience best for programming

MS Teams Video Interviews

1st - HM interview round – 45 minutes max

2nd - Panel technical round - 45 minutes max – potential exercise / caste study component

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