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# Enterprise Data Lake Lead

- **Company:** Data Inc
- **Location:** Houston, TX, United States (Remote available)
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Amazon Web Services, Business Analytics Applications, Apache HTTP Server, Architectural Patterns, Microsoft Azure, Bash Shell, Big Data, C Sharp (Programming Language), Cloud Computing, Cluster Analysis, Computer Programming, Databases, Data Discovery, Information Engineering, Data Governance, Data Migration, Relational Databases, Database Design, Database Queries, Identity and Access Management, PostgreSQL, Meta-Data Management, Microsoft SQL Server, SQL Azure, MySQL, Performance Tuning, Query Optimization, Azure Active Directory, Cloud Services, DataOps, Shell Script, SQL Stored Procedures, SQL Server Reporting Services, SQL Server Integration Services, Data Streaming, Transact-SQL, Enterprise Data Management, Azure Service Bus, Data Classification, Azure Data Factory, Istio, Database Optimization, Apache Spark, Multi-Cloud, Change Data Capture, Database Migration, Data Lakes, Debezium, Kubernetes, Data Lineage, Collibra, Deployment Automation, Apache Kafka, Azure AKS, Cloudwatch, Terraform, Stream Processing, Key Vault, Databricks, Programming Languages
- **Published:** October 28, 2026
- **Apply:** https://www.dice.com/job-detail/ff96d508-293c-4e10-acad-a797d5d62a10

## About the Role

Technical Expertise around 12-15 years of experience.

Data Streaming & Processing

5+ years with Apache Kafka (streaming architecture, Kafka Connect, Schema Registry, stream processing)

3+ years with Databricks (Delta Lake, Apache Spark optimization, Unity Catalog, cluster management)

Deep understanding of data lake architecture patterns (Bronze/Silver/Gold, medallion architecture)

Data Governance & Cataloging

3+ years with DataHub or similar metadata management platforms (Alation, Collibra, Apache Atlas)

Deep experience building and operating enterprise data catalog systems

Expertise in automated metadata extraction, lineage tracking, and impact analysis

Experience with data quality frameworks and metadata-driven data operations

Knowledge of data governance policies, data classification, and compliance automation

Understanding of data discovery, access control, and self-service analytics enablement

Relational Database Systems

5+ years with enterprise RDBMS platforms including:

SQL Server(T-SQL, SSIS, SSRS, replication, Always On Availability Groups)

PostgreSQL(advanced query optimization, partitioning, extensions, streaming replication)

MySQL(replication, clustering, performance tuning)

Strong SQL skills (complex queries, stored procedures, window functions, query optimization)

Database design principles (normalization, indexing strategies, schema design, partitioning)

Change Data Capture (CDC) patterns and implementation (Debezium, Azure Data Factory, AWS DMS, custom solutions)

Database migration experience (schema migration, data migration, zero-downtime migrations)

Cloud & Infrastructure

5+ years with Azure or AWS Cloud including:

Azure: Data Lake Storage (Gen2), Event Hubs, AKS, Azure SQL, Key Vault, Azure AD, Monitor

AWS: S3, MSK/Kinesis, EKS, RDS/Aurora, Secrets Manager, IAM, CloudWatch

Cloud-native data services, networking, security, and IAM

3+ years with Kubernetes (deployment strategies, scaling, monitoring, service mesh, Helm)

3+ years with Terraform (modules, state management, multi-environment deployments, multi-cloud)

Programming & Development

Strong proficiency in any programming languages like C#, Go

Expert-levelSQLacross multiple database platforms

Experience with Python for data engineering tasks (preferred)

Familiarity with Shell scripting (Bash)

Leadership & Experience

7+ yearsin data engineering, platform engineering, or database engineering roles

3+ yearsin technical leadership capacity (Tech Lead, Principal Engineer)

Proven track record of delivering large-scale data infrastructure projects

Experience leading teams of 5-10+ engineers

Strong architectural design and system thinking capabilities

Experience migrating legacy RDBMS workloads to modern data lake architectures

Demonstrated ability to balance technical excellence with business needs