Sr Data Engineer

Sr Data Engineer

RIT Solutions

Austin, TX • On-site

$113.50K - $136.30K/yr

Other

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Job description

Senior Data Engineer

If you love turning complex, high-volume data into trusted, reusable products—this role is for you. We're looking for a

Senior Data Engineer

to design and deliver modern ELT pipelines, scalable architectures, and analytics-ready datasets that accelerate engineers, analysts, and data scientists. You'll lead with strong engineering fundamentals, partner across teams, and help set the standards for how data is built and used.

What You'll Do

  • Design, develop, optimize, and maintain data architecture + ELT pipelines aligned to business outcomes
  • Architect and implement end-to-end data solutions (warehouses/lakes, pipelines, models, products)
  • Solve complex data challenges to deliver insights and enable decision-making at scale
  • Build data products that boost productivity for engineers, analysts, and data scientists
  • Engineer high-quality features for modeling in close collaboration with data scientists and business partners
  • Lead evaluation and deployment of emerging analytics engineering tools/processes
  • Define and drive best practices, standards, and operational excellence (quality, stability, reuse, scale)
  • Mentor junior engineers; lead design discussions and cross-functional collaboration
  • Partner with ML engineers, BI, and solutions architects on strategic enterprise initiatives
  • Communicate and enable teams through education plans on standards, capabilities, and processes

What We're Looking For

  • Deep understanding of distributed computing, scalability, and data architecture
  • Strong critical thinking and ability to tackle big data challenges end-to-end
  • Proficiency with data warehouses/lakes and big data technologies (e.g., Spark/Databricks, Snowflake/Redshift, distributed databases)
  • Expertise in ELT + SQL and data analysis (advanced SQL required)
  • Modern pipeline practices and tooling (e.g., dbt, Airflow, Spark, Python and OSS data ecosystem)
  • Strong software engineering fundamentals and tooling (Git, CI/CD, JIRA); comfort in Linux + Bash/Z shell
  • Cloud experience building data/analytics solutions (GCP; Azure also valued)
  • Familiarity with BI tools (e.g., Power BI, Tableau, Looker, Alteryx)
  • Knowledge of dimensional modeling, governance concepts, and structured/unstructured data

Education & Experience Needed

  • Bachelor's degree in Computer Science, Statistics, Engineering, or related field
  • 7 or more years of total experience in data engineering or analytics engineering



Frequently asked questions

Q: What skills or qualities help someone succeed as a Data Software Engineer?

A: To succeed as a Data Software Engineer, key technical skills include proficiency in programming languages such as Python, Java, or C++, as well as expertise in data structures, algorithms, and software development methodologies like Agile. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial, as Data Software Engineers often work with cross-functional teams and stakeholders to design, develop, and deploy data-driven solutions. By combining technical expertise with strong soft skills, Data Software Engineers can effectively drive business outcomes, innovate, and adapt to the rapidly evolving landscape of data technology.

Q: What is the career path for a Data Software Engineer?

A: A Data Software Engineer's typical career progression involves starting as a Junior Software Engineer, where they focus on developing and maintaining data-driven software applications, and gradually advancing to roles such as Senior Software Engineer, Technical Lead, or Data Architect, where they oversee large-scale data systems and lead cross-functional teams. Key opportunities for skill development include learning programming languages like Python, SQL, and Java, as well as data science tools like Hadoop, Spark, and machine learning frameworks like TensorFlow and PyTorch. Long-term, Data Software Engineers may pursue leadership roles, such as Director of Engineering or Chief Technology Officer, or transition into related fields like data science, product management, or entrepreneurship.