Merkle
(Senior)DataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“(Senior) Data Engineer at Merkle. Skills: Big data architecture, Data pipelines, Cloud services, Machine learning models. Design data ingestion. Implement data ingestion”
Industry & Context.
Optimizing existing data delivery; Re-designing infrastructure for greater scalability; Optimizing machine learning models; Optimizing data algorithms
What They're Looking For.
Must Have
3-7 years of experience in a Data Engineer role, Experience in building and productionizing big data architectures, Experience in building and productionizing data pipelines, Experience in building and productionizing data sets, Understanding data concepts and patterns of big data, Understanding data concepts and patterns of data lake, Understanding data concepts and patterns of lambda architecture, Understanding data concepts and patterns of stream processing, Understanding data concepts and patterns of DWH, Understanding data concepts and patterns of BI, Advanced Python programming, Experience with other object-oriented languages, Experience with functional languages, Experience with scripting languages, Data related services from Azure, Data related services from AWS, Data related services from GCP, Big data technologies like Databricks, Big data technologies like Fabricm, Big data technologies like AWS Glue, Big data technologies like Snowflake, Big data technologies like Dataproc, Big data technologies like BigQuery, Extensive working experience with relational databases, Extensive working experience with NoSQL databases, Streaming technology services like Kafka, Streaming technology services like Event Hubs, Streaming technology services like Kinesis, Orchestration services like dbt, Orchestration services like Airflow, Orchestration services like Cloud Composer, Orchestration services like AWS Step Functions, Orchestration services like AWS Lambda, Orchestration services like Azure Functions, Compute services like dbt, Compute services like Airflow, Compute services like Cloud Composer, Compute services like AWS Step Functions, Compute services like AWS Lambda, Compute services like Azure Functions, ETL services like dbt, ETL services like Airflow, ETL services like Cloud Composer, ETL services like AWS Step Functions, ETL services like AWS Lambda, ETL services like Azure Functions, Analytic skills related to structured datasets, Analytic skills related to unstructured datasets, Build processes supporting data transformation, Build processes supporting data structures, Build processes supporting metadata, Build processes supporting dependency management, Build processes supporting workload management, Experience in setting up CI/CD automation tools, Experience in using CI/CD automation tools, Person who is precise, Person who is well organized, Can adapt to changing circumstances, Not afraid of responsibility
Nice to Have
Experience in delivery of business intelligence projects, Understanding of web-tracking frameworks, Experience with Salesforce Cloud services
What You'll Do.
Design data ingestion
Implement data ingestion
Design data processing
Implement data processing
Work with stakeholders
Assist with data-related technical issues
Support data infrastructure needs
Optimize existing data delivery
Re-design infrastructure for scalability
Collaborate with Business Intelligence consultants
Assemble large data sets
Assemble complex data sets
Support machine learning teams
Deploy Machine Learning models
Optimize Machine Learning models
Deploy data algorithms
Optimize data algorithms
Develop data pipelines
Provide actionable insights
Use infrastructure as code
Automate release automation pipelines
Document data pipelines
Plan activities using Agile methodology
Propose technical solutions
Estimate effort accurately
How You'll Work.
Team & Collaboration
International team; Data architects; Data scientists; Business Intelligence consultants; Machine learning teams
Process & Methodology
Agile methodology
Full Job Description
**Job Description:** **We Dream. We Do. We Deliver.** Merkle, a dentsu company, powers the experience economy. For more than 35 years, the company has put people at the heart of its approach to digital business transformation. As the only integrated experience consultancy in the world with a heritage in data science and business performance, Merkle delivers holistic, end-to-end experiences that drive growth, engagement, and loyalty. Merkle's expertise has earned recognition as a "Leader" by top industry analyst firms, in categories such as digital transformation and commerce, experience design, engineering and technology integration, digital marketing, data science, CRM and loyalty, and customer data management. With more than 16,000 employees, Merkle operates in 30+ countries throughout the Americas, EMEA, and APAC. For more information, visit www.merkle.com. **Who are we looking for** We are now looking for a savvy **Data Engineer** to join our team of data heroes! We are open to both mid level and senior profiles. You will be responsible for designing and building big data architecture pipelines for data lake houses in cloud, as well as optimizing and productionizing machine learning and predictive models. The ideal candidate is an experienced software engineer and data wrangler who enjoys building complex platforms from the ground up, using the latest technologies in cloud. You will cooperate with data architects and data scientists on large data projects for the biggest international brands, as well as build an internal platform framework to ensure consistent & optimal delivery. You should be a versatile self-starter eager to roll out next-gen data architectures, comfortable supporting multiple technologies/teams/solutions/clients, and also a great team player able to work within our international team with a positive, startup-minded attitude. **What will you do** * Design and implement data ingestion and processing of various data sources using public cloud se
Applying for this (Senior) Data Engineer role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Workday
- Workday has a multi-step form — save your progress after every section.
- "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
- Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
- Job requisition numbers are useful when following up with HR by email.
ANONYMOUS · UNFILTERED
What do employees actually say about Merkle?
Real rants from real employees. Read before you apply.