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About Job
We are seeking an experienced Data Engineer to join our data team. As a Senior Data Engineer, you will work on various data engineering tasks including designing and optimizing data pipelines, data modelling, and troubleshooting data issues. You will collaborate with other data team members, stakeholders, and data scientists to provide data-driven insights and solutions to the organization. Experience required is of 3+ Years.
Responsibilities:
Design and optimize data pipelines for various data sources
Design and implement efficient data storage and retrieval mechanisms
Develop data modelling solutions and data validation mechanisms
Troubleshoot data-related issues and recommend process improvements
Collaborate with data scientists and stakeholders to provide data-driven insights and solutions
Coach and mentor junior data engineers in the team
Skills Required:
3+ years of experience in data engineering or related field
Strong experience in designing and optimizing data pipelines, and data modelling
Strong proficiency in programming languages Python
Experience with big data technologies like Hadoop, Spark, and Hive
Experience with cloud data services such as AWS, Azure, and GCP
Strong experience with database technologies like SQL, NoSQL, and data warehousing
Knowledge of distributed computing and storage systems
Understanding of DevOps and power automate and Microsoft Fabric will be an added advantage
Strong analytical and problem-solving skills
Excellent communication and collaboration skills
Qualifications
Bachelor's degree in Computer Science, Data Science, or a Computer related field (Master's degree preferred)
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
1. Communicate with the clients and understand their business requirements.
2. Build, train, and manage your own team of junior data engineers.
3. Assemble large, complex data sets that meet the client’s business requirements.
4. Identify, design and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
5. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources, including the cloud.
6. Assist clients with data-related technical issues and support their data infrastructure requirements.
7. Work with data scientists and analytics experts to strive for greater functionality.
Skills required: (experience with at least most of these)
1. Experience with Big Data tools-Hadoop, Spark, Apache Beam, Kafka etc.
2. Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
3. Experience in ETL and Data Warehousing.
4. Experience and firm understanding of relational and non-relational databases like MySQL, MS SQL Server, Postgres, MongoDB, Cassandra etc.
5. Experience with cloud platforms like AWS, GCP and Azure.
6. Experience with workflow management using tools like Apache Airflow.