Data Engineer - Technical Lead - Technology

Company Description

About Merkle

Merkle, a dentsu company, is a leading data-driven customer experience management (CXM) company that specializes in the delivery of unique, personalized customer experiences across platforms and devices. For more than 30 years, Fortune 1000 companies and leading nonprofit organizations have partnered with Merkle to maximize the value of their customer portfolios. The company’s heritage in data, technology, and analytics forms the foundation for its unmatched skills in understanding consumer insights that drive hyper-personalized marketing strategies. Its combined strengths in consulting, creative, media, analytics, data, identity, CX/commerce, technology, and loyalty & promotions drive improved marketing results and competitive advantage. With more than 14,000 employees, Merkle is headquartered in Columbia, Maryland, with 50+ additional offices throughout the Americas, EMEA, and APAC. For more information, contact Merkle at
1-877-9-Merkle or visit www.merkle.com.

Job Description

Additional Roles & Responsibilities:

• Apply strong technical skills in a data engineering team building industry-leading technology

• Embrace an active team role to help design, implement, and launch efficient and reliable data pipelines moving data across a number of platforms including Data Warehouse, online caches and real-time systems

• Create data architecture that is flexible, scalable, and consistent for cross-functional use, and aligned to stakeholder business requirements

• Deploy workflow orchestration and demonstrate expertise in data modeling, ETL development, and data warehousing

• Build industry-leading tools to increase productivity of Data Analysts, Data Scientists and Marketers

• Help Marketing organization to become a 100% data-driven organization by building a next generation data platform that brings accurate and timely data to the Marketers

• Validate Data Engineering business data elements, organizational and business intelligence architecture designs for engineering functional areas from Dashboards, Data Lakes, Data Operations, ML - AI, and upstream/downstream intake and output processes

•  4+ years of industry experience in data engineering, data science, or related field with a track record of manipulating, processing, and extracting value from large datasets

• Experience building and managing data pipelines and repositories in cloud environments such as Google Cloud, Microsoft Azure or AWS

• Experience in Airflow is a must

• Experience extracting/cleansing data and generating insights from large transactional data sets using Spark SQL, SQL, Python, and PySpark on cloud

• Experience with optimizing Spark pipelines on Dataproc, Databricks or similar technologies

• Strong verbal and written communications skills at all levels; ability to communicate complex customer behavior information to both functional partners and Executive Leadership

• Open to idea exploration with strong problem-solving/analytical abilities

• Demonstrated strength in creating partnerships and in building relationships with other functions and associates within the organization

Qualifications

BA/BS Degree in Computer Science, any Engineering discipline, Statistics, Information Systems or another quantitative field

Additional Information

Good to have skills:

Python
GCP (Big Query)
Spotfire/Qlikview/PowerBI
Supervised and unsupervised machine learning techniques (clustering, decision Tableau
Modeling techniques (linear regression, logistic regression, forecasting)
SQL
Ensemble modeling, XGBoost, text mining
Analytics Services
IC Senior
Sr. Analyst
Hive, Spark (PySpark), Hadoop, Big data environment
Specific areas of expertise
Retail, e-commerce domain