Remote Sr. Data Engineer

Description:

• Lakeshore is seeking a Sr. Data Engineer to enhance data insights for internal stakeholders through collaboration across teams.
• The role involves implementing data quality, observability, and lineage frameworks, including monitoring, alerting, and automated remediation for pipeline failures.
• Responsibilities include data cleanup, requirements gathering, data modeling and transformation, report and dashboard creation, and data mining and analytics on complex datasets.
• A solid grounding in data security, privacy, and governance is required.
• The ideal candidate should have over 5 years of hands-on data engineering experience, including ownership of mission-critical pipelines in production.
• Daily tasks include designing, building, and owning production data pipelines using tools like Apache Airflow, Matillion, and SSIS, ensuring robust orchestration, auto-scaling, and fault tolerance.
• The role requires integrating data across various systems (ERP, CRM, e-commerce, IoT, and third-party APIs) using REST/GraphQL, Kafka, CDC tools, SFTP, and event-streaming patterns.
• The candidate will develop and evolve data foundation architectures (Redshift, SQL Server) for both batch and real-time use cases.
• Collaboration with Analytics, BI, and Data Science teams is essential to deliver reusable semantic models for Qlik, Power BI, and Excel.
• The candidate will champion engineering excellence through CI/CD for data code, infrastructure-as-code (Terraform/CDK), Git-based workflows, and peer code reviews.
• Responsibilities also include performing root-cause analysis and optimization of SQL, Python, and integration workflows.
• The candidate will partner closely with platform, security, and DevOps teams to align on best practices for governance, cost control, and compliance.
• Ensuring reliability and performance of data pipelines by monitoring orchestration workflows and conducting root cause analysis of failures and performance issues is crucial.

Requirements:

• Candidates must have over 5 years of hands-on data engineering experience, including ownership of mission-critical pipelines in production.
• Experience in designing dimensional and domain-driven data models to support BI and self-service analytics is required.
• Deep expertise with SQL (T-SQL, Redshift SQL) and performance tuning for large-scale analytics workloads is necessary.
• Hands-on experience with Git for version control and GitHub Actions for CI/CD automation is essential.
• The candidate should demonstrate the ability to lead projects, influence cross-functional stakeholders, and elevate engineering standards through partnership and collaboration.
• Proven mastery of modern ETL/ELT and orchestration frameworks (Airflow, AWS Glue, Matillion, and SSIS) and at least one cloud platform (AWS strongly preferred) is required.
• A strong understanding of integration patterns—batch, streaming, CDC—and technologies such as Kafka, Kinesis, Debezium, or Azure Event Hubs is necessary.
• Proficiency in Python (Pandas, PySpark) for data transformation and automation is required; familiarity with Scala or Java is a plus.
• A solid grounding in data security, privacy, and governance (encryption, IAM, RBAC, PII handling, and GDPR/CCPA awareness) is essential.

Benefits:

• Lakeshore offers a salary range between $102,500 - $143,500 for this position, depending on relevant experience and skillset.
• The position is bonus eligible.
• Paid leave for new parents is provided to support work/life balance and family bonding.
• Employees receive excellent medical/dental and vision coverage, including EPO, PPO, and HSA options.
• A 401(k) retirement plan with company contribution is available.
• Flexible benefits allow employees to choose what they like and ignore the rest.
• On-site preschool is available for employees’ children.
• An on-site employee gym is provided for all fitness levels and needs.
• Employees enjoy a generous discount on products.
• A casual dress code is encouraged.