Technology Lead - AWS Data Engineer

Infosys; Burnaby; On-site; CAD 90,000 - 137,000; Full time

Job summary

Infosys is seeking an experienced Data Engineer with 6+ years of hands-on experience to build scalable data platforms and ETL pipelines. The ideal candidate excels in AWS Athena, Scala, and Apache Spark, and designs data lake solutions in AWS with performance tuning.

Required are a Bachelor's degree (or equivalent), Canadian work eligibility, 4+ years IT experience, and willingness to relocate to Burnaby, BC. Travel may be required.

Qualifications

• Bachelor’s degree or foreign equivalent required; three years of progressive experience may substitute education.
• Authorized to work in Canada without employer sponsorship; Infosys cannot sponsor visas.
• At least 4 years of information technology experience.
• Must be located within commuting distance of Burnaby, BC or willing to relocate; travel may be required.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Scala and Apache Spark.
• Build and optimize data processing workflows for large-scale datasets.
• Develop and manage data lake solutions using AWS S3, Athena, Glue, and EMR.
• Optimize Athena queries, partitions, and storage formats to reduce costs.
• Collaborate with Data Architects, Analysts, and Stakeholders to deliver data solutions.
• Tune Spark jobs with optimized joins, partitioning, caching, and shuffles; support CI/CD deployments.
• Participate in Agile ceremonies, code reviews, and technical design discussions.

Skills

ETL pipeline design

Spark performance tuning

Data architecture collaboration

SQL proficiency

CI/CD understanding

Education

Bachelor’s degree or equivalent

Tools

AWS Athena

Scala

Apache Spark

AWS S3

AWS Glue

AWS EMR

IAM

CloudWatch

Git

Job description

Infosys is seeking an experienced Data Engineer with 6+ years of experience in building scalable data platforms and ETL pipelines. The ideal candidate should have strong hands‑on expertise in AWS Athena, Scala, and Apache Spark, with experience designing and optimizing large-scale data processing solutions in AWS environments. Experience with AWS data lake architectures, performance tuning, and distributed data processing is essential. The requirements align with enterprise data engineering practices found in internal data engineering profiles and job descriptions.

Required Qualifications

• Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
• Candidates authorized to work for any employer in Canada without employer based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time.
• At least 4 years of Information Technology experience
• Candidate must be located within commuting distance of Burnaby, BC or be willing to relocate to one of these areas. This position may require travel.

Preferred Qualifications

• Design, develop, and maintain scalable ETL/ELT pipelines using Scala and Apache Spark.
• Build and optimize data processing workflows for large-scale structured and semi-structured datasets.
• Develop and manage data lake solutions using AWS S3, Athena, Glue, and EMR.
• Optimize Athena queries, partitions, and data storage formats to improve performance and reduce costs.
• Implement data quality checks, validation frameworks, and monitoring solutions.
• Integrate data from multiple sources including databases, APIs, streaming platforms, and flat files.
• Collaborate with Data Architects, Analysts, and Business Stakeholders to deliver data solutions.
• Tune Spark jobs by optimizing joins, partitioning, caching, and shuffle operations.
• Support CI/CD deployments, release management, and production issue resolution.
• Participate in Agile ceremonies, code reviews, and technical design discussions.
• At least 6 years of experience in Data Engineering.
• Strong hands‑on experience with AWS Athena.
• Strong development experience in Scala.
• Expertise in Apache Spark (Spark Core, Spark SQL).
• Experience with AWS services such as S3, Glue, EMR, IAM, CloudWatch.
• Strong SQL and data modeling skills.
• Experience building and maintaining ETL/ELT pipelines.
• Good understanding of distributed data processing and performance tuning.
• Experience with Git and CI/CD practices.

Job entails sitting as well as working at a computer for extended periods of time. Should be able to communicate by telephone, email or face to face. Travel may be required as per the job requirements.

Estimated annual compensation range for the candidate based in the below location will be:

British Columbia - $ 90450 to $ 136500

Additional Required Qualifications

• Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
• Candidates authorized to work for any employer in Canada without employer based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time.

About Us

Infosys is a global leader in next‑generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI‑powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always‑on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.

EEO

Infosys provides equal employment opportunities to applicants and employees without regard to race; color; sex; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.