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Data Modeller (Dimensional Modelling & SQL Focus)
Core Responsibilities:
Design and implement dimensional data models (star/snowflake schemas) optimized for reporting and analytics.
.Key Skills:
Deep understanding of data warehousing principles and Kimball/Inmon methodologies.
Expertise in SQL, Databricks SQL, and data cataloging tools.
Ability to work with source system SMEs to understand data lineage and semantics. Reporting
Relevance :Ensures data structures are optimized for Power BI, Tableau, or other BI tools, enabling performant and intuitive reporting.
Job Description
Mandatory Requirements
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Experience in AWS Glue
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Experience in Apache Parquet
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Proficient in AWS S3 and data lake
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Knowledge of Snowflake
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Understanding of file-based ingestion best practices.
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Scripting language - Python & pyspark
CORE RESPONSIBILITIES
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Create and manage cloud resources in AWS
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Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies
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Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform
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Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations
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Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
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Define process improvement opportunities to optimize data collection, insights and displays.
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Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible
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Identify and interpret trends and patterns from complex data sets
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Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders.
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Key participant in regular Scrum ceremonies with the agile teams
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Proficient at developing queries, writing reports and presenting findings
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Mentor junior members and bring best industry practices.
QUALIFICATIONS
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5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales)
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Strong background in math, statistics, computer science, data science or related discipline
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Advanced knowledge one of language: Java, Scala, Python, C#
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Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake
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Proficient with
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Data mining/programming tools (e.g. SAS, SQL, R, Python)
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Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
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Data visualization (e.g. Tableau, Looker, MicroStrategy)
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Comfortable learning about and deploying new technologies and tools.
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Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines.
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Good written and oral communication skills and ability to present results to non-technical audiences
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Knowledge of business intelligence and analytical tools, technologies and techniques.
Familiarity and experience in the following is a plus:
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AWS certification
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Spark Streaming
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Kafka Streaming / Kafka Connect
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ELK Stack
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Cassandra / MongoDB
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CI/CD: Jenkins, GitLab, Jira, Confluence other related tools

