Senior Data Engineer

Senior Data Engineer

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Job Description

As a Senior Data Engineer, you will serve as the chief technical lead solving our clients’ complex technical problems by architecting creative, scalable solutions. You will help formalize a Data Engineering team at Saatchi and build data pipelines for advanced analysis.

This role will have a strong focus on data integration, modeling, automation, optimization, governance and reusability. You will work with teams of passionate data professionals responsible for supporting all analytics, business intelligence, data science and reporting needs across the organization. An ideal candidate should have hands-on experience working with large data sets, finding the best ways to engineer the data to help develop critical KPI metrics.

Success for this position is measured by the wide scale adoption of (internal and client) architectural design, development, implementation and maintenance of data processing pipelines that focuses on scalability, low-latency, and fault-tolerance. Other success factors include excellent demonstration of writing complex, highly optimized queries across large data sets; as well as the ability to upskill current staff with software engineering principles, domain knowledge and product development skills.

• Providing marketing business solutions by developing strategy, managing implementation, and reporting on the performance of large-scale, high visibility analytical projects (e.g., CRO models, ML/AI)
• Creating or optimizing current ETL processes, employing and recommending a variety of data integration and data preparation tools, or writing code — such as Scala, Python and Java
• Acquire data from primary or secondary data source platforms (on-prem or cloud) and maintain databases/data systems to empower operational and exploratory analysis for analysts/developers
• Performing initial data exploration steps (e.g., profiling, understanding data quality, binning, finding correlations) and validating proposed solution design with testing approach, POCs, and deployment to production servers using Agile methodology and DataOps best practices
• Architecting, building and delivering new data models in collaboration with information stewards that automate analyses in accordance with governance practices
• Monitoring analytics platform and infrastructure performance, escalating issues as needed
• Enthusiastically leading and growing a team of junior data professionals by providing guidance, technical instruction, inspirational leadership, and performance management on a regular basis
• Interpreting data, bringing analytical rigor with statistical techniques to reporting deliverables
• The ability to work extended hours, including weekends, as required
• All other duties as assigned

Qualifications

• Bachelor's degree from such STEM programs as Computer Science, Engineering, MIS, Operations Research, Mathematics, Statistics, etc. A graduate degree in a similar field is a plus.
• 5+ years of experience in data engineering work within the digital marketing domain (i.e., analytics development or implementation, architecture of relational databases, validating data quality)
• 3+ years of experience orchestrating ETL workflows and authoring pipelines using modern Software Development best practices, including automated builds, tests and deployment in BI tools or through scripting in SQL, NOSQL, Java, Scala or Python
• 3+ years of supervisory experience, coaching team members on gaining technical expertise in data engineering
• 2+ years of experience using and administering data visualization techniques with Tableau, PowerBI, Domo, Superset, Matplotlib, Plotly and/or similar tools
• Experience in application deployment tools and architectures like Jenkins, Kubernetes, Docker, Microservices
• Familiar with CI/CD
• Experience with data streaming tools like RabbitMQ, Kafka, Pulsar
• Knowledge of the digital marketing media space, including common KPIs and multi-touch attribution (MTA) and other methods used to measure ad effectiveness
• Strong written and verbal presentation skills: can clearly identify and translate business challenges with reporting results that tie back to program/campaign objectives, and bridge the gap between technology and business stakeholders
• Strong attention to detail and ability to prioritize tasks, multitask and manage time effectively using Agile methodology
• Automotive or retail industry experience is a major plus

• Digital Media Platforms: Adobe Analytics, Google Cloud Platform (GA360, ADH, BigQuery), Oracle
• Big Data Administration: AWS, Azure, Oracle, Cloudera, Hue
• Data Flow Architecture: MSSQL, Hadoop, Kubernetes, Spark, Kafka, Airflow
• Modeling and Querying: SQL (PostgreSQL, Redshift), Python (via Anaconda), R (via Rstudio), Scala, Hive, Impala, Pig, Matlab, SAS, Java
• ETL Tools: SSIS, Alteryx, Talend, Power Query, Fivetran, Stitch, Informatica
• Machine Learning applications including API development and deployment in the cloud

Additional Information

All your information will be kept confidential according to EEO guidelines.