Harmonya

Experience Requirements:

• 5+ years of experience in a Customer Success or Account Manager role

• Customer/Shopper Insights, Category Management, Analytics experience in a CPG or Retailer preferred

• Experience working in a fast-growing startup and technology environment, specifically in B2B SaaS data/analytics and CPG

• Proven track record of being able to successfully onboard and support customers with new data sets, platforms, or technologies

• Demonstrated ability to build lasting relationships, deliver high customer satisfaction, and build loyalty based on mutual value creation

Other Requirements:

• Strong presentation skills, experience preparing for in person presentations often with multiple stakeholders

• Empathy to truly understand customer problems and needs and work internally and externally to address customer needs

• Curiosity, creativity, patience, and an entrepreneurial mindset are critical to success in this role.

• High accountability, integrity, and attention to detail

• Excellent verbal and written communication skills

• Familiarity with common CPG and Retail industry data sets - NielsenIQ, Circana, Luminate, 84.51, Numerator, Mintel, etc

Responsibilities:

• Build strategic relationships with CPG and Retail companies

• Lead post-sale and sustain engagements with clients and ensure they derive as much value as possible from our technology and capabilities

• Proactively identify and solve client problems, and identify new opportunities where Harmonya can address with our clients

• Serve as a trusted partner to clients externally and be your client’s advocate internally to help us achieve our goal of developing long lasting and collaborative relationships

• Collaborate with our network of partners to provide the best possible experience to our clients as they onboard and operationalize our capabilities

Experience Requirements:

• 6+ years of experience in data or backend engineering

• Demonstrated experience in designing, developing, and delivering sophisticated data applications

• Hands-on experience with data pipeline orchestration and data processing tools, particularly Apache Airflow and Spark.

• Deep experience with public cloud platforms, preferably GCP, and expertise in cloud-based data storage and processing.

• Excellent communication skills and the ability to collaborate effectively with cross-functional teams.

Other Requirements:

• Ability to thrive under pressure, consistently delivering results, and making strategic prioritization decisions in challenging situations.

• Bachelor's degree in Computer Science, Information Technology, or a related field or equivalent experience.

• Familiarity with data science tools and libraries.

• Experience with Docker containers and Kubernetes

Responsibilities:

• Design, implement, and optimize scalable data pipelines for efficient data processing and analysis.

• Build and maintain robust data acquisition systems to gather, process, and store data from various sources.

• Work closely with DevOps engineers, Data Science and Product teams to understand their requirements and provide data solutions that meet business objectives.

• Proactively monitor data pipelines and production environments to identify and resolve issues promptly.

• Implement best practices for data security, integrity, and performance.

Experience Requirements:

• At least 6 years of experience in software engineering in Python or an equivalent language

• At least 3 years of experience with data engineering products from early-stage concept to production rollouts

• Experience with cloud platforms (GCP, AWS, Azure), working on production payloads at large scale and complexity

• Hands-on experience with data pipeline building and tools (Luigi, Airflow etc), specifically on cloud infrastructure

Other Requirements:

• Advantage: Hands-on experience with relevant data analysis tools (Jupyter notebooks, Anaconda etc)

• Advantage: Hands-on experience with data science tools, packages, and frameworks

• Advantage: Hands-on experience with ETL Flows

• Advantage: Hands-on experience with Docker / Kubernetes

Responsibilities:

• Design and build data acquisition pipelines that acquire, clean, and structure large datasets to form the basis of our data platform and IP

• Design and build data pipelines integrating many different data sources and forms

• Define architecture, evaluate tools and open source projects to use within our environment

• Develop and maintain features in production to serve our customers

• Collaborate with product managers, data scientists, data analysts and full-stack engineers to deliver our product to top tier retail customers