Data Engineer

Key Skills

Amazon RedShift, AWS, Azure, Confluence, Data Analytics, Data Modeling, Data Warehousing, ETL/ELT technologies, Git, Google Cloud Platform (GCP), JIRA, Project management, Snowflake, SQL, SQL Server, XML-JSON

Job Description

Description and Requirements

At BMC trust is not just a word - it's a way of life!

We are an award-winning, equal opportunity, culturally diverse, fun place to be. Giving back to the community drives us to be better every single day. Our work environment allows you to balance your priorities, because we know you will bring your best every day. We will champion your wins and shout them from the rooftops. Your peers will inspire, drive, support you, and make you laugh out loud!  

We help our customers free up time and space to become an Autonomous Digital Enterprise that conquers the opportunities ahead - and are relentless in the pursuit of innovation! 

Description and Requirements

We are the BMC-Operations Analytics & Data Science team, a highly functional, growing, business & outcome-focused team that enables business groups within BMC to make better decisions centered around our customers. Through our analysis, applications, and insights, we empower our users with insight while supporting and leading strategic initiatives across our entire organization.

It's an exciting time at BMC! Your energy and passion for data will help drive our Autonomous Digital Enterprise (ADE) roadmap to a Best in Class data-driven and customer-centric organization. 

And teamwork makes it happen! We are looking for a talented, disciplined, results-driven, and passionate individual data engineer (lead data infrastructure initiatives & integrations) with seamless people skills connecting various stakeholders and audiences around a shared vision & strategy.

NOTE: In addition to your resume/C.V., after submitting your application, our Recruitment team will ask that you prepare a brief to describe a few of the most challenging problems and business issues that you solved & how you solved them. 

The Role: 

You will play a key role in our Analytics & Data Science developing & collaborating on strategic data initiatives focused on

• Lead data engineering projects across the business (Marketing, Sales, Customer Success, Product R&D, etc.), including planning, coordinating resources, and ensuring the successful delivery of projects to ensure alignment and delivery of data to extract insights across the customer journey
• Develop and maintain data pipelines for extracting, transforming, and loading data from various sources into data warehouses or data lakes. This includes designing and implementing ETL processes, data transformations, and data quality checks.
• Lead data modeling efforts, ensuring optimal performance and data integrity. Implement database strategies and oversee database management activities for scalability, security, and adherence to best practices.
• Collaborating with data scientists, business analysts, and other stakeholders to understand data requirements and provide the necessary support
• Strong project management skills, technical expertise, and the ability to provide guidance and mentorship to team members are essential for success in this role.
• Design, develop and maintain engineering best practices in data security, compliance, retention, and sensitivity.
• Creating and maintaining documentation for data structures, ETL processes, and data lineage

Skills and Experience

Must-Have's

• Five or more years of experience in data modeling, data warehousing, building enterprise-level data integrations and data pipelines.
• Proficiency in SQL, query tuning, and optimization on various relational databases
• Two or more years of experience with building solutions on cloud platforms including AWS, GCP, Azure or OCI
• Proficiency in SQL, query tuning & optimization on Snowflake, MS SQL Server, RedShift, or other Relational Data bases
• Proficiency in Python, Spark for data extraction, manipulation, data pipelines, and data integrations
• Experience in working with different data types, structured, semi-structured and unstructured. This includes understanding data formats such as JSON, XML, parquet, and CSV and being proficient in handling diverse data sources.
• Experience in designing data integration, data pipelines & lifecycle management, version control (Git, Bitbucket, etc.), documentation (confluence, etc.), and familiarity with the agile framework (Jira, etc.)
• Experience supporting data scientists & analysts in data analytics workflows
• Ability to work effectively in a dynamic, business-growth-focused group that has several concurrent projects

Nice to have:

• SaaS Software industry experience business preferable