Database Engineer II-

As a
Database Engineer II
at
Tekion
, you will design, automate, and optimize database operations across our cloud-native automotive retail platform connecting OEMs, dealerships, partners, and consumers.

This role requires strong expertise in
Python, SQL/PL-SQL, JavaScript (for MongoDB)
, and
data structures & algorithms
, with a deep focus on
problem-solving and automation
.

Exposure to
AI/ML technologies
is a plus.
Key Responsibilities

• Python Automation (Primary Focus):
• Develop reliable and reusable Python scripts to automate key database operations such as schema migrations, health checks, data validation, and performance optimization.
• SQL & PL/SQL Development:
• Write and optimize
  complex SQL queries
  ,
  stored procedures
  ,
  functions
  , and
  triggers
  for MySQL/PostgreSQL.
• Develop and manage
  PL/SQL logic
  for data manipulation, validation, and reporting.
• Perform schema design, indexing, and query plan optimization to enhance performance.
• MongoDB Scripting:
• Use
  JavaScript and Python
  for MongoDB scripting, aggregation, data cleanup, and performance improvement tasks.
• Algorithmic Problem Solving (Core Skill):
• Apply
  data structures and algorithms
  to solve real-world data and system challenges efficiently.
• Design
  Python-based programs
  that automate or optimize database workflows using algorithmic thinking.
• Example problem areas candidates should be comfortable with:
• Finding duplicates or missing records in large datasets.
• Comparing data consistency between source and target databases.
• Implementing retry, queue, or scheduling logic using stacks/queues.
• Detecting outliers or anomalies in performance metrics or logs.
• Writing scripts to identify circular dependencies in database relationships.
• Optimizing time complexity in Python scripts that process millions of records.
• Designing scripts to summarize large log files or analyze trends.
• Building mini utilities for automation — like config diff tools or schema comparison programs.
• Monitoring & Troubleshooting:
• Build monitoring automation to detect replication issues, latency spikes, or performance degradation and auto-trigger alerts or recovery actions.
• DevOps & Cloud Integration:
• Integrate with CI/CD pipelines and cloud services (AWS, Azure, GCP) to automate provisioning, deployment, and backups.
• Performance Optimization:
• Tune SQL queries, database configurations, and scripts for efficiency, scalability, and reliability.
• Collaboration & Compliance:
• Partner with DBAs, developers, and product teams to maintain operational standards, security, and compliance.

Qualifications & Skills

Must Have:

• Strong proficiency in
  Python
  for automation, scripting, and algorithmic problem solving.
• Hands-on expertise in
  SQL and PL/SQL
  for MySQL/PostgreSQL.
• Proficiency in
  JavaScript (for MongoDB)
  scripting and operations.
• Strong understanding of
  Data Structures and Algorithms (DSA)
  — arrays, linked lists, trees, graphs, hashing, recursion, etc.
• Excellent analytical and debugging skills with a logical mindset.
• Experience with
  cloud platforms
  (AWS, Azure, or GCP) and managed database services like RDS or DynamoDB.
• Familiarity with
  DevOps tools
  (Git, Jenkins, Terraform, etc.).
• Good communication skills and ability to collaborate across teams.

Nice to Have:

• Experience with
  AI/ML integration
  , such as using models for anomaly detection or predictive performance insights.
• Experience with database performance tuning, replication, or sharding.
• Familiarity with monitoring and observability tools (Grafana, Prometheus, Datadog).
• Knowledge of infrastructure automation (Ansible, Chef, Terraform).
• Exposure to distributed database systems such as MongoDB Atlas or Aurora.

Education

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

What We're Looking For

We're seeking a
hands-on engineer
who:

• Codes efficiently in
  Python, SQL, PL/SQL, and JavaScript
  .
• Thinks algorithmically and solves complex problems creatively.
• Automates repetitive database tasks with precision and scalability.
• Understands both
  SQL and NoSQL
  performance tuning.
• Brings curiosity, ownership, and innovation — including openness to
  AI-driven solutions
  for database management.