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Senior Data Engineer
Synechron
- Mississauga, Ontario, Canada
- Mississauga, Ontario, Canada
À propos
At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron's progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 16,400+, and has 60 offices in 20 countries within key global markets.
Our challenge
We are seeking a highly skilled and experienced Data Engineer to join our growing data team. This role will be instrumental in designing, building, optimizing, and maintaining our robust data infrastructure and pipelines. The candidate will work with cutting-edge big data technologies to ingest, process, store, and transform large datasets, enabling advanced analytics and machine learning initiatives across the organization. The ideal candidate will have a deep understanding of data warehousing, ETL/ELT processes, and a passion for building scalable and reliable data solutions.
Additional Information*
The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within Mississauga, ON is CAD$110k -CAD$125k/year & benefits (see below).
The Role
Responsibilities:
Design, develop, and maintain scalable and efficient data pipelines using Apache Spark, Java Spark, PySpark, and Apache Flink for real-time and batch processing of large datasets.
Implement and manage data storage solutions leveraging Hadoop Distributed File System (HDFS) and data lake table formats like Apache Iceberg.
Build and optimize data models and schema definitions for various data sources and targets, ensuring data quality, consistency, and accessibility.
Work with stakeholders to understand data requirements, translate them into technical specifications, and deliver robust data solutions.
Monitor, troubleshoot, and optimize existing data pipelines and infrastructure for performance, reliability, and cost-efficiency.
Develop and implement data governance, security, and compliance best practices within the data ecosystem.
Collaborate with data scientists, analysts, and other engineering teams to support their data needs and integrate new data sources.
Evaluate and recommend new technologies and methodologies to enhance our data platform capabilities.
Ensure proper documentation of data architectures, pipelines, and processes.
Requirements:
Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
Proven experience as a Data Engineer or in a similar role building and optimizing "big data" data pipelines, architectures, and data sets.
Strong proficiency in programming languages such as Python (with extensive PySpark experience), Java, or Scala.
Expertise in Apache Spark for data processing, including Spark SQL, DataFrames, and RDDs.
Hands-on experience with Apache Hadoop ecosystem components, particularly HDFS.
Experience with real-time stream processing using Apache Flink.
Familiarity with data lake table formats, specifically Apache Iceberg, for managing large, evolving datasets.
Experience with relational SQL and NoSQL databases.
Solid understanding of ETL/ELT processes, data warehousing concepts, and data modeling techniques.
Good to have experience with cloud platforms (AWS, Azure, GCP) and their data services.
Excellent problem-solving, analytical, and communication skills.
Preferred skills:
Experience with containerization and orchestration tools like Docker and Kubernetes.
Knowledge of DevOps practices related to data pipelines.
Familiarity with machine learning workflows and MLOps.
We offer:
A multinational organization with 60 offices in 20 countries and the possibility to work abroad.
15 days (3 weeks) of paid annual leave plus an additional 10 days of personal leave (floating days and sick days).
A comprehensive insurance plan including medical, dental, vision, life insurance, and long-term disability.
Flexible hybrid policy.
RRSP with employer's contribution up to 4%.
A higher education certification policy.
On-demand Udemy for Business for all Synechron employees with free access to more than 5000 curated courses.
Coaching opportunities with experienced colleagues from our Financial Innovation Labs (FinLabs) and Center of Excellences (CoE) groups.
Cutting edge projects at the world's leading tier-one banks, financial institutions and insurance firms.
A truly diverse, fun-loving and global work culture.
S YNECHRON'S DIVERSITY & INCLUSION STATEMENT
Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative 'Same Difference' is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.
All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant's gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.
Compétences linguistiques
- English
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