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Metro locations and broad technical stack increase applicant density, while DBA specialization limits some competition.
Data platform and DBA expertise transfers across industries but requires domain-specific experience.
Explicit 6-10 years requirement plus mandatory DBA, big-data and tooling skills create strict filters.
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Own database administration responsibilities including database design, normalization, server tuning, and query plan optimization for large datastores with HA and DR planning.
Develop and deploy software solutions using Java, Scala, Python, and database programming languages (ANSI SQL, TSQL, PL/pgSQL, PLSQL).
Operate and optimize big data tools (Kafka, Spark, Trino/Presto), orchestration tools (Airflow), and container management via Docker and Kubernetes including DevOps deployment and application tuning.
6+ years of professional DBA experience managing large datastores including HA and DR support.
Proficiency with database languages such as ANSI SQL, TSQL, PL/pgSQL, and PLSQL, plus database design and optimization.
Experience with big data tools such as Kafka, Spark, and Trino/Presto, and orchestration tools like Airflow.
Experience with containerization technologies Docker and Kubernetes, plus DevOps deployment and monitoring tools like Datadog, Prometheus, Grafana, or Cloudwatch.
Experienced in both database administration and software engineering across backend languages such as Java, Scala, and Python indicating strong cross-functional capability.
Hands-on with big data ecosystem and data pipeline orchestration reflecting a data-centric development environment.
Comfortable with modern DevOps, containerization, and monitoring toolchains indicating operational ownership and end-to-end delivery responsibility.