Job description

We are looking for a Software Engineer with Python expertise to guide customers with technical onboarding and product adoption. As part of the role, you may help build new product features, develop custom scripts, or provide product training to address customer needs. This is a hybrid role where you are part of Customer Success but will work closely with the Engineering, Product, and Ingestion teams.

We are growing fast. Our customers range from startups to Fortune 500 companies across industries and continents. You will be assigned a set of accounts aligned with your time zone. You will work closely with data engineers, scientists, and analysts in customer organizations to help them adopt our products and best practices to achieve their goals.

Our main products are data catalog and observability. Acryl Data provides clarity to data by enabling delightful search and discovery, data observability, and federated governance across organizations' entire data ecosystem. Started as a technology at LinkedIn, Acryl has grown to become the largest open-source metadata platform. Our community has 10,000 members across thousands of organizations. Acryl Data was founded by experts who previously created LinkedIn DataHub and Airbnb Dataportal and is backed by top venture capital firms.

As a Software Engineer, you will have the opportunity to shape the Customer Success function and work with a collaborative and tight-knit team. Acryl Data is committed to building a diverse and inclusive environment and offers competitive salaries, health benefits, and generous stock options.

Key Responsibilities

Provide advanced technical support via multiple channels (Slack, ZenDesk, Zoom).
Troubleshoot and resolve technical issues promptly.
Collaborate with product engineering teams to resolve complex customer problems.
Deliver proactive customer success initiatives, including onboarding, training, and ongoing product optimization as required.
Monitor customer health metrics and help drive retention by identifying patterns of usage and product gaps.

Qualifications

5+ years of experience in software engineering or data engineering
Expertise in Python and experience working with the modern data stack, data pipelines, and ELT processes in an enterprise environment
Expertise in SQL, modern data warehouses, transformation tools, and BI tools such as Snowflake, BigQuery, dbt, Airflow, Tableau, Looker, etc
Excellent communication and interpersonal skills
Passion for helping customers
Comfortable working in a fast-paced startup environment
Bachelor's degree in Computer Science

This position is open to candidates in all time zones of the United States and Europe and can be done remotely.

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