Big Data Developer

Avance Services — Canada · Posted ~1 day ago

Senior

Skills

Apache Spark Scala PySpark Kafka Hadoop HDFS Hive Impala NoSQL HBase MongoDB Couchbase Distributed computing ETL Data pipelines SQL Data modeling

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Summary ✨ AI‑Generated

Work as a Big Data Developer on large-scale data processing systems. You will build ETL and data pipelines using distributed technologies, work with batch and real-time workloads, and apply strong SQL and data-modeling skills to complex datasets.

Highlights

Opportunity to work on large-scale data platforms and sophisticated batch and real-time processing use cases, with exposure to distributed computing and financial-sector applications.

Description

Spark Scala Developer Mississauga, Ontario | Calgary, Alberta Required Qualifications: At least 6 years of Information Technology experience6+ years of experience in Big Data technologies.Strong expertise in:Apache Spark (Core, SQL, DataFrames, RDDs)Scala programmingPySparkHands-on experience with:Kafka (real-time streaming)Hadoop ecosystem (HDFS, Hive, Impala)NoSQL Databases (HBase, MongoDB, Couchbase)Strong understanding of distributed computing concepts and data processing frameworks.Experience in building ETL/data pipelines for large-scale datasets.Proficiency in SQL and data modeling. Preferred Qualifications: Hands-on experience with data lakes, data warehouses, and scalable ETL pipeline design, including batch and real-time processing architecture.Strong understanding and practical exposure to Agile software development methodologies (Scrum) and SDLC practices.Proven experience in Banking domain, supporting use cases such as fraud detection, risk analytics, regulatory reporting, and customer insights.Excellent analytical, problem-solving, and communication skills, with the ability to translate business requirements into scalable technical solutions.Demonstrated ability to work effectively in cross-functional, multi-stakeholder environments, collaborating with Business, Data Engineering, and Architecture teams.Experience with real-time data streaming frameworks such as Kafka and Spark Streaming for low-latency processing.Understanding data modeling concepts (dimensional modeling, snowflake schemas) to support analytics workloads.Experience and desire to work in a global delivery environment.