Data Integration Engineer
General overview of the role
Join us as a Data Integration Engineer consolidating data from across our enterprise as a key component to delivering amazing support experiences at scale. In Support.com engineering, we are refreshing our data stack around Snowflake. Help us grow our time series data analytic capabilities to derive insights based on agent and consumer support interactions. Analyze our support content and its usage to provide feedback into content authoring and presentation. Come and imagine a future where real time support data streams fuel machine learning algorithms that customize support to provide an optimal consumer experience.
Build, maintain and deploy the integration infrastructure for ingesting high-volume support data from consumer interactions, devices, and apps across a myriad collection of software solutions.
Design and implement the processes that turn data into insights. Model and mine the data to describe the system's behavior and to predict future actions.
Develop and maintain the data-related code in an automated CI/CD build/test/deploy environment
Research individually and in collaboration with other teams on how to solve problems
B.E/BTech/MCA/MTech/M. E from an accredited university or college (domestic or international).
5+ years of experience working in a consumer internet or software company is required and 3+ years of relevant work experience; but, really, we are open to any developer that has the technical prowess
Excellent programming skills in Python with bonus points for Java, Java, or Scala experience
Direct experience with some of the following; Snowflake, Fivetran, S3, Apache Spark, Airflow, and PostgreSQL or substantially similar tools
Ability to understand business problems and translate them into technical requirements
A reliable and fast internet connection and stable power supply to enable work from home.
Ability to benchmark systems, analyze system bottlenecks and performance issues and design solutions to eliminate them.
Ability to evaluate and clearly articulate pris and cons of various technical approaches related to data gathering.
Ability to work effectively and collaboratively from home.
Skills considered as a good plus
Experience with a modern Big Data processing stack including Fivetran, Kafka, Kinesis or equivalent technologies
Strong knowledge of traditional Data Warehouse-related components (Sourcing, ETL, Data Modeling, Infrastructure, BI, Reporting)
Competitive benefits and compensation!
A flexible but challenging work from home experience!
Ability to work with exceptionally creative and talented people!