Growth Marketing Big Data Engineer

Key Skills

3D data processing, Aartificial intelligence, Algorithms, Apache Cassandra, Apache Hadoop, Apache Hive, Apache Kafka, Apache Pig, Big Data Technology, Data pipelines, Data science techniques, Database, ETL frameworks, Flume, Growth Analytics, HBase, Machine learning techniques, MapReduce, MongoDB, NoSQL, Python Programming, R Programming, RabbitMQ, Scrum Agile Methodology, SPARK Programming, SQL

Job Description

What you’ll achieve

As a Growth Marketing Big Data Engineer, you will deliver models and solutions that will be the essential ingredient, we use to supply our customers & sales with relevant product recommendations and creative breakthroughs to our business. You will work with other engineers and data scientists to solve some of the hardest business problems. You will learn what it takes to build, deploy & scale ML/AI models in real-world (it’s a hard problem, we assure you). You will build analytical data sets on which model’s will be built. This would entail two key tasks – feature engineering on large datasets and optimization of our pipelines to drive scalability. If you are already good at it, we will make you better.

You will:

• Feature engineering: Stitching together and aggregation of multiple large data sets working with the data scientist to a desired format. You will need to optimize both queries and architecture to support big data sets. SQL is usually the preferred language, but some NoSQL or Spark jobs are necessary
• Implement complex Data pipelining / ETL process: Once the initial dataset are prepared, it is normally run through a further pipeline to prepare it for modelling. Here you will create features that make ML/AI algorithms work (e.g., translating text into category variables). Python/R is usually the preferred language
• Develop and maintain documentation
• Producing ad hoc datasets and reports

Take the first step towards your dream career

Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role:

Essential Requirements:

• Intermediate SQL & Python/R skills
• Education (Bachelor’s degree or higher) in Computer Science, Mathematics, or a related technical field, or equivalent practical experience
• Proven ability to work with varied data infrastructures – including relational databases, column stores, Json format
• You have professional experience. 1+ years of experience in Data or BI engineering dealing with large complex data scenarios
• Experience of ETL and data processing as well as experience working in an Agile environment and SCRUM methodologies

Desirable requirements:

• Experience with data processing software (such as Hadoop, Spark, Pig, Hive), along with data processing algorithms (MapReduce, Flume) and with stream data processing tools such Kafka, RabbitMQ
• Experience with monitoring tools such Dynatrace, NewRelic, Splunk and with other NoSQL databases such MongoDB, Cassandra, HBase, and file-based storage solutions

Who we are

We believe that each of us has the power to make an impact. That’s why we put our team members at the center of everything we do. If you’re looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we’re looking for you.

Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us.

Application closing date: 22 October 2023

Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy here.

Job ID:R233231

Dell’s Flexible & Hybrid Work Culture

At Dell Technologies, we believe our best work is done when flexibility is offered.

We know that freedom and flexibility are crucial to all our employees no matter where you are located and our flexible and hybrid work style allows team members to have the freedom to ideate, be innovative, and drive results their way. To learn more about our work culture, please visit our locations page.