Steneral Consulting hiring Data Engineer - Tech Lead || Remote - No PST || Full time only in United States | LinkedIn (2024)

Data Engineer - Tech Lead100% Remote - No PST Candidates

Here were a few of my notes from our conversation with Kelly:

She want someone in CST Timezone.

Top 3 Skills Needed

• Strong programming languages - she mentioned strong SQL at first but in talking with her about the MuleSoft piece, she really needs someone who has also worked with development languages, preferably Java. She wants someone who brings the mindset of both a data engineer as well as a programmer, as this person will be a tech lead over a couple junior MuleSoft developers ad she wants someone ultimately who can help guide them in how to think differently in their approaches to MuleSoft development.
• Traditional data engineering skills: ETL/ELT, Data warehousing, creating data pipelines;
• Experience with Cloud Data platforms – they use Azure predominantly with a little AWS. Not particular on which cloud platform a candidate has used Correct

Projects supporting: could work on Life strategy or Business Transformation Modernization; needs MuleSoft if supporting BTM;

Years of experience: She would like 3-5 years experience as a tech lead, leading, guiding junior team members and providing technical direction as well as helping to coach them on different ways to think through different technical challenges.

Reason for need: This role is both a backfill and growth, someone is not working out who was in a different time zone and finding it difficult to maintain a schedule that aligns with the team.

Location: Really needs someone onsite, strong preference bordering on a hard requirement. If not, at the very least must be in central time zone. IF remote in CST, MuleSoft would need to be required, (I feel)

They have been using MuleSoft/API management for 3 years and considers it fairly mature at this point, but the developers are more junior and while they are doing well, they are limited in their overall experience and maturity in how to handle more advanced technical problems. This Tech Lead doesn’t need to have a ton of MuleSoft experience, but people with no exposure to it and only coming from a SQL/ETL background struggle to pick it up and provide leadership with it because the mindset is so different.

Must Have’s

• Life Insurance and Annuities industry experience.
• Strong data engineering experience
• Tech Lead experience
• MuleSoft
• API Management
• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 10+ years of IT development experience.
• 5+ years of experience in designing and implementing enterprise data solutions.
• Proficiency in cloud data platforms such as AWS, Azure, PCF or Google Cloud Platform.
• Proven experience publishing and managing Kafka topics.
• Proven experience as a Data Engineer, preferably in the insurance or financial services industry.
• Strong expertise in data modeling, ETL/ELT processes, and data warehousing concepts.
• Hands-on experience with programming languages (Python, Java, or Scala) and SQL.
• Strong understanding of data governance, metadata management, data quality controls, data lineage and data security.
• Experience working in an Agile environment with strong Scrum framework knowledge.
• Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.
• Experience with modern data & integration tools or technologies such as Snowflake, ADL (Azure Data Lake) /ADF (Azure Data Factory), MuleSoft technology is a plus.

Job DescriptionTitle: Data Engineer - Tech LeadInterview Process: Two Rounds

Position OverviewWe are seeking a highly skilled and motivated Data Engineer with expertise in cloud-based data integration to join our dynamic team. The ideal candidate will play a pivotal role in designing, developing, and maintaining robust data pipelines and systems to support our insurance and annuity products.

Responsibilities

• Design, implement, and manage scalable data pipelines for ingesting, transforming, and storing diverse data sets from various sources into our cloud-based data infrastructure.
• Develops, tests, and deploys code using internal software development toolsets, including the code for deploying infrastructure and solutions for secure data storage, ETL pipelines, data catalogs and data queries.
• Collaborate with cross-functional teams to understand data requirements and develop solutions that meet business objectives.
• Optimize data workflows and processes for efficiency, reliability, cost and performance.
• Ensure data quality, integrity, and security throughout the data lifecycle.
• Stay updated with emerging technologies and best practices in data engineering, cloud services, and integration methodologies to drive continuous improvement.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 10+ years of IT development experience.
• 5+ years of experience in designing and implementing enterprise data solutions.
• Proficiency in cloud data platforms such as AWS, Azure, PCF or Google Cloud Platform.
• Proven experience publishing and managing Kafka topics.
• Proven experience as a Data Engineer, preferably in the insurance or financial services industry.
• Strong expertise in data modeling, ETL/ELT processes, and data warehousing concepts.
• Hands-on experience with programming languages (Python, Java, or Scala) and SQL.
• Strong understanding of data governance, metadata management, data quality controls, data lineage and data security.
• Experience working in an Agile environment with strong Scrum framework knowledge.
• Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.
• Experience with modern data & integration tools or technologies such as Snowflake, ADL (Azure Data Lake) /ADF (Azure Data Factory), MuleSoft technology is a plus.

Preferred Qualifications

• Experience with API management.
• Advanced degree in a relevant field.
• Industry certifications related to cloud services or data engineering.
• Experience with specific tools or technologies relevant to insurance data analysis or actuarial science.