Data Ops Engineer - Software Engineer - Technology

Company Description About Merkle Merkle, a subsidiary of Dentsu, is a premier data-driven customer experience management (CXM) company. It specializes in delivering unique, individualized customer experiences across various platforms and devices. For over 30 years, Merkle has partnered with Fortune 1000 companies and leading nonprofit organizations to optimize the value of their customer portfolios. The company's expertise in data, technology, and analytics contributes to its unparalleled ability to comprehend consumer insights which drive highly personalized marketing strategies. Merkle's combined strength in consulting, creative development, media, analytics, data, identity, CX/commerce, technology, and loyalty & promotions contribute to improved marketing results and competitive advantage. With more than 14,000 employees, Merkle's headquarters is in Columbia, Maryland, and it operates over 50 additional offices throughout the Americas, EMEA, and APAC regions. For more information, contact Merkle at 1-877-9-Merkle or visit www.merkle.com. Job Description Additional Roles & Responsibilities: - Demonstrate strong technical skills within a data engineering team building industry-leading technology. - Participate actively in a team role to help design, implement, and launch efficient and reliable data pipelines moving data across various platforms including Data Warehouse, online caches, and real-time systems. - Develop a flexible, scalable, and consistent data architecture for cross-functional use and aligned with stakeholder business requirements. - Implement workflow orchestration and show expertise in data modeling, ETL development, and data warehousing. - Create industry-leading tools to boost the productivity of Data Analysts, Data Scientists, and Marketers. - Assist the Marketing organization to become a 100% data-driven organization by constructing a next-generation data platform that provides accurate and timely data to Marketers. - Validate Data Engineering business data elements, organizational and business intelligence architecture designs for engineering functional areas, including Dashboards, Data Lakes, Data Operations, ML - AI, and upstream/downstream intake and output processes. - Have 4+ years of industry experience in data engineering, data science, or a related field with a history of manipulating, processing, and extracting value from vast datasets. - Have experience in building and managing data pipelines and repositories in cloud environments such as Google Cloud, Microsoft Azure, or AWS. - Experience in Airflow is essential. - Have experience in extracting/cleansing data and generating insights from extensive transactional datasets using Spark SQL, SQL, Python, and PySpark on the cloud. - Have experience with optimizing Spark pipelines on Dataproc, Databricks, or similar technologies. - Demonstrate strong communication skills, both verbal and written, at all levels; ability to articulate complex customer behavior information to functional partners and Executive Leadership. - Be open to idea exploration with strong problem-solving/analytical abilities. - Show strength in creating partnerships and building relationships with other functions and associates within the organization. Qualifications - A 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.