Data Engineer & Database Administrator

· Design and optimize data models in PostgreSQL, MongoDB, and Amazon Redshift

· Develop and manage data workflows using AWS (S3, Glue, Lambda, Step Functions, Kinesis)

· Administer and maintain database environments across development, staging, and production

· Monitor data pipelines and databases, troubleshoot issues, and implement alerts

· Optimize query performance, indexes, and configurations across relational and NoSQL systems

· Manage database provisioning, upgrades, backups, and disaster recovery (RDS, MongoDB, Redshift)

· Ensure database security, including access control, encryption, and role management

· Plan capacity and scale systems to support growing data needs

· Define and enforce data retention and archival policies

· Collaborate with analytics and product teams to support reporting and data needs

· Document data pipelines, database processes, and operational procedures

· Participate in code reviews and follow engineering best practices

· Design, build and maintain ETL/ELT pipelines across multiple systems, Bachelor's degree in Computer Science, Engineering, or a related field - or equivalent experience.

3-5 years of Data Engineering Experience or equivalent experience

Qualifications:

· 3-5 years of experience in data engineering, database administration, or similar roles

· Strong experience with PostgreSQL, MongoDB, and Amazon Redshift

· Solid SQL skills for both transactional and analytical workloads

· Experience with AWS data and database services (S3, Glue, Lambda, RDS, Redshift, etc.)

· Proficiency in Python or another scripting language

· Experience with workflow orchestration tools (Airflow, Step Functions, etc.)

· Hands-on database administration experience, including:

· MongoDB (replica sets, sharding, indexing, backups)

· Redshift (cluster management, query tuning, WLM, snapshots)

· PostgreSQL (replication, performance tuning, connection pooling)

· Familiarity with monitoring tools (CloudWatch, pgBadger, MongoDB Atlas, etc.)

· Understanding of database security (encryption, auditing, least-privilege access)

· Strong problem-solving and analytical skills

· Ability to translate business needs into data solutions

· Comfortable working in a fast-paced, collaborative environment

· Clear communicator with both technical and non-technical audiences

· Self-motivated with a focus on clean, maintainable code

Nice to Have

· Experience with Kafka or Kinesis (streaming data)

· Familiarity with dbt for data transformation

· Knowledge of data lake/lakehouse architectures (Delta Lake, AWS Lake Formation)

· Experience with Terraform or CloudFormation

· CI/CD experience for data pipelines

· Basic DevOps skills