Senior Data Engineer

Job title: Senior Data Engineer

About the Role Merkle, a dentsu company, is seeking a Data Engineer to design and build big data architectures and data lakehouse pipelines in the cloud. You will collaborate with data architects and data scientists to deliver scalable data platforms for large international brands, and help productionize ML models and analytics. The role welcomes both mid-level and senior profiles and requires a hands-on, startup-minded attitude.

What You'll Do

• Design and implement data ingestion and processing of various data sources using public cloud services.
• Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs, like optimizing existing data delivery, re-designing infrastructure for greater scalability, etc.
• Collaborate with Business Intelligence consultants and assemble large and complex data sets that meet functional and non-functional business requirements for data lakehouse.
• Support machine learning teams in deployment and optimization of AI / Machine Learning models and other data algorithms.
• Develop data pipelines to provide actionable insights into marketing automation, customer acquisition and other key businesses areas.
• Use infrastructure as a code and CI/CD tools to automate release automation pipelines.
• Document data pipelines and logic in a structured manner using Confluence, plan your activities using Agile methodology in Jira.
• Support pre-sales by proposing technical solutions and accurate effort estimation.

What We're Looking For

• Experience in building and productionizing big data architectures, pipelines and data sets.
• Understanding data concepts and patterns of big data, data lake, lambda architecture, stream processing, DWH, and BI.
• 3-7 years of experience in a Data Engineer role, with experience using the following software/tools: Advanced Python programming.
• Experience with other object-oriented / functional / scripting languages like Bash, Scala, Java, R, PowerShell etc.
• Data related services from Azure, AWS, and GCP public clouds.
• Big data technologies like Databricks, Fabricm, AWS Glue, Snowflake, Dataproc, BigQuery, etc.
• Relational databases like MS SQL, Postgres, Aurora DB and NoSQL databases like DynamoDB, MongoDB, Elasticsearch, Redis, etc.
• Streaming technology services like Kafka, Event Hubs, and Kinesis, etc.
• Orchestration, compute, and ETL services like dbt, Airflow, Cloud Composer, AWS Step Functions, AWS Lambda, Azure Functions etc.
• Strong analytic skills related to working with structured and unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• Experience in setting up and using CI/CD automation tools like Azure DevOps, GitHub actions, Jenkins, etc.
• Personal traits: precise, well organized, good communication skills, adaptable, responsible.

Nice to Have

• Experience in delivery of business intelligence projects, using tools like Power BI, Tableau, Looker.
• Understanding of web-tracking frameworks such as Adobe Analytics and Google Analytics.
• Experience with Salesforce Cloud services.