Lead I - Software Engineering

Lead I - Software Engineering

The associate data engineer is an early-career engineer learning the full hr analytics data engineering vertical hands-on — from ingestion, through modeling and transformation, into the microsoft fabric semantic layer and power bi visualizations.

The associate data engineer takes well-defined components of solution designs that senior and data engineers have shaped, and turns them into working, tested, documented code under the guidance of more senior engineers on the team.

The role is structured to build technical depth and domain context steadily over time, with a clear growth path into the data engineer role as the engineer earns autonomy and ownership.

The associate data engineer must be located in the country.

The hr analytics engineering team operates as a single team across the country and india, with clear layers and a shared way of working: the hr analytics engineering team is structured in three layers that work together: an information architect who owns end-to-end architecture and engineering standards; principal data engineers who set the engineering bar and lead the data engineering team; and senior data engineers, data engineers, and associate data engineers who deliver data products across the full vertical.

The team operates across the country (frisco, tx) and india (hyderabad) and incountry locations in pst timezone, with engineers in all regions partnering across the timezone gap to keep delivery moving and to share ownership of data products end-to-end.

Business engagement happens through the team's senior engineering and architecture leadership, with broader engineering team participation that grows over time as engineers build domain context and earn trust with stakeholders.

Work flows from a business need into a technical solution design, then into a build that spans ingestion through the unified framework, data modeling, transformation across snowflake and databricks, semantic layer in microsoft fabric, and visualization in power bi — with quality, testing, documentation, and reliability owned across the whole vertical.

The team operates a devops model — engineers own their data products in production, share an on-call schedule, and rotate the operations role across the team.

This role is an early-career engineer who learns the full vertical hands-on, contributing under the guidance of senior engineers on the team and growing into broader ownership as skills and context develop.

Senior and data engineers on the hr analytics team identify authoritative sources, model the data, and decompose business objectives into technical designs that span ingestion, transformation, semantic layer, and visualization.

The associate data engineer contributes to those designs in well-scoped pieces: implements assigned ingestion components within the team's unified ingestion framework.

Builds assigned transformation and modeling components in snowflake (including iceberg tables) and databricks (delta lake) under the guidance of senior engineers. Implements unit tests, data quality checks, and reconciliation for assigned work.

Builds assigned semantic layer components in microsoft fabric and visualization components in power bi per the design.

Helps operate and maintain data products after delivery, including monitoring and incident response with senior engineer support.

Over time, the associate data engineer grows toward more independent ownership of components and eventually full data products, as preparation for promotion to data engineer.

Core responsibilities

Execute assigned components of solution designs handed off by senior and data engineers, delivering production-grade code under senior engineer guidance.

Land source data into the team's unified ingestion framework using the patterns specified in the design.

Implement assigned data models and transformation logic in snowflake (including iceberg tables) and databricks (delta lake, unity catalog) per the design.

Apply medallion (bronze, silver, gold) architecture and the team's engineering standards to all work, including naming conventions, documentation, and code review practices.

Build assigned components of the semantic layer in microsoft fabric (fabric iq, onelake) per the design specifications.

Build assigned power bi visualizations and reports following the design specifications and the team's bi standards. Implement unit tests, data quality checks, and reconciliation for assigned work. Help operate assigned data products after delivery, including monitoring, alerting, and incident response with support from senior engineers.

Write and maintain documentation including source-to-target mappings, data lineage, data dictionaries, and runbooks for assigned work.

Contribute to and follow the team's devops practices — git, ci/cd, automated testing, and code review.

Participate actively in design reviews and team discussions, asking clarifying questions and learning from senior engineers' perspectives.

Build hr domain context steadily over time — attending stakeholder meetings as appropriate, asking questions, and growing the foundation for future business engagement.

Collaborate with the broader engineering team and share what you learn through demos and informal knowledge sharing.

Required qualifications:

Bachelor's degree in computer science, software engineering, information management, or equivalent experience in field — plus 1+ years of related work experience, or equivalent demonstrated experience through internships, bootcamps, or self-directed project work. Must be located in the country.

1+ years of hands-on data engineering or software engineering experience, including internships and academic project work that demonstrate production-quality engineering habits.

Working proficiency in sql and python.

Exposure to spark (pyspark or spark sql) for distributed data transformation, or strong willingness and demonstrated ability to learn it quickly.

Exposure to cloud data platforms — databricks, snowflake, or comparable — with a willingness to develop hands-on depth.

Familiarity with at least one bi tool (power bi preferred, tableau or similar acceptable).

Understanding of fundamental data engineering concepts ” data modeling, etl/elt, data quality, source-to-target mapping.

Familiarity with git, code review practices, and basic ci/cd concepts.

Good communication skills — able to ask clarifying questions, communicate progress clearly, and learn from feedback.

Strong problem-solving instincts, curiosity, and the discipline to deliver well-defined work to a high standard.

Eagerness to learn the full vertical from ingestion through visualization, and to take on broader ownership over time.

Preferred qualifications

Hands-on coursework, internship, or project experience with databricks (delta lake) or snowflake at any scale. Hands-on coursework, internship, or project experience with microsoft fabric, onelake, or power bi.

Exposure to iceberg tables or other modern open table formats. Exposure to hr data domains — talent acquisition, workforce analytics, compensation, learning, performance, or people analytics.

Familiarity with workday, servicenow hr, or comparable hr systems of record.

Exposure to streaming technologies (kafka, azure event hub, delta live tables, or spark structured streaming).

Exposure to ai/ml pipelines or building data products that support ml workloads.

Azure certifications (azure fundamentals, data engineer associate) or working toward them.

Familiarity with t-mobile's omni lakehouse platform, magentabuilt integrations, or enterprise it architecture standards.

Familiarity with data privacy concepts (gdpr, ccpa) and hr data handling considerations.

Tekwissen® group is an equal opportunity employer supporting workforce diversity.