Position: Sr. Data Engineer/Analyst
Location; Palo Alto, CA
We're hiring a hands-on Senior Data Engineer/Analyst to be part of Data Solutions organization. The data solutions team builds out tools and infrastructure needed to source, validate, clean and process the data and build compelling reports for leaders. Our team is looking for a Senior Data Architect to help scale our data efforts. If you have passion for data and want to help build Intapp's next gen data platform that provide actionable insights to drive customer and business outcomes, we'd love to hear from you.
You will contribute to the full software development life cycle, including design, modeling, data migrations, unit testing, performance tuning, deployment activities.
What you'll do:
Understand complex business requirements and translates into technical specifications
You can single-handedly build highly scalable end-to-end data ingestion pipelines using different open source tools and operationalizing them.
Build infrastructure for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, cloud based relational or non-relational databases employing ETL tools and/or scripting languages like Perl/Python and streaming technologies like Kafka, Kinesis.
Apply technologies to solve complex data problems with expert knowledge in programming languages like SQL, Python, Linux, SQL, Hive, Spark.
Build and deploy dashboards using one or more visualization tools such as tableau, Power BI
Define optimized DB schemas that power the compelling story-telling dashboards.
Work with stakeholders including Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs
Uses highest level of subject matter expertise to decide on data modeling, data sourcing, data quality, and BI delivery solutions
Define SLA and acceptable time lags by data source, define QA process, and socialize resolution process to ensure data accuracy and consistency.
Ideal Candidate Must-Haves
BA/BS Degree in Computer Science, any Engineering discipline, and 3+ years of experience in relevant Data engineering and Business Intelligence platforms or Master's degree in Computer
Science, any Engineering discipline / information technology and 3+ years in relevant Data
engineering and Business Intelligence platforms experience
Relational SQL and NoSQL databases
Tableau, Domo or other reporting tools
Advanced SQL; experience with working on large multidimensional data sets, unstructured data.
Data Pipelines such has Kafka, Kinesis, Pyspark
ETL Tools such as Informatica, Talend, Dell Boomi
Experience working with AWS components [EC2, S3, DynamoDB]
Big data tools Hadoop, Hive, HDFS, Spark etc.
Experience in CI/CD pipelines
Demonstrated proficiency implementing self-service solutions to empower an organization to generate valuable actionable insights
Setup, maintain, and implement Kafka topics and processes