Senior Data Architect

Arkhya Tech. Inc.; Dallas (TX); On-site; USD 120,000 - 150,000; Full time

Job summary

A leading tech firm in Dallas, Texas, seeks an experienced data engineer to lead the migration of a SQL data warehouse to a Data Lake on Google Cloud. The successful candidate will design data models, build ingestion pipelines, and utilize advanced analytics for data-driven decision-making. A Bachelor's or Master's in Computer Science and 10+ years of relevant experience is needed. Google Cloud certification is required, and a competitive salary is offered, reflecting experience and expertise.

Qualifications

• 10–14 years in data engineering/architecture required.
• 5+ years of experience designing solutions on GCP.
• Google Cloud Professional Cloud Architect certification required.

Responsibilities

• Migrate data warehouse to a Data Lake on GCP.
• Design data models optimized for analytics.
• Build batch and streaming ingestion pipelines using GCP services.

Skills

Data engineering

Cloud Computing (GCP)

BigQuery SQL

Data modeling

Python programming

Data ingestion pipelines

Education

Bachelor’s/Master’s in Computer Science, Information Systems

Tools

BigQuery

Dataflow

Apache Beam

Cloud Composer

Apache Spark

Job description

Overview

Contract

Project/Program

Identity & Access Management (IAM) Data Modernization – migration of an on‑premises SQL data warehouse to a target‑state Data Lake on Google Cloud (GCP), enabling metrics & reporting, advanced analytics, and GenAI use cases (natural language querying, accelerated summarization, cross‑domain trend analysis).

About Program/Project

The IAM Data Modernization project involves migrating an on-premises SQL data warehouse to a target state Data Lake in GCP cloud environment. Key highlights include:

• Integration Scope: 30+ source system data ingestions and multiple downstream integrations
• Capabilities: Metrics, reporting, and Gen AI use cases with natural language querying, advanced pattern/trend analysis, faster summarizations, and cross-domain metric monitoring
• Scalability and access to advanced cloud functionality
• Highly available and performant semantic layer with historical data support
• Unified data strategy for executive reporting, analytics, and Gen AI across cyber domains

This modernization establishes a single source of truth for enterprise-wide data-driven decision-making.

Data Lake Architecture & Storage

• Proven experience designing and implementing data lake architectures (e.g., Bronze/Silver/Gold or layered models).
• Strong knowledge of Cloud Storage (GCS) design, including bucket layout, naming conventions, lifecycle policies, and access controls

Experience with Hadoop/HDFS architecture, distributed file systems, and data locality principles

• Hands-on experience with columnar data formats (Parquet, Avro, ORC) and compression techniques
• Expertise in partitioning strategies, backfills, and large-scale data organization
• Ability to design data models optimized for analytics and BI consumption

Qualifications

• Experience: [10–14]+ years in data engineering/architecture, 5+ years designing on GCP at scale; prior on‑prem → cloud migration a must.
• Education: Bachelor’s/Master’s in Computer Science, Information Systems, or equivalent experience.
• Certifications: Google Cloud Professional Cloud Architect (required or within 3 months). Plus: Professional Data Engineer, Security Engineer.

Data Ingestion & Orchestration

• Experience building batch and streaming ingestion pipelines using GCP-native services
• Knowledge of Pub/Sub-based streaming architectures, event schema design, and versioning
• Strong understanding of incremental ingestion and CDC patterns, including idempotency and deduplication
• Hands-on experience with workflow orchestration tools (Cloud Composer / Airflow)
• Ability to design robust error handling, replay, and backfill mechanisms

Data Processing & Transformation

• Experience developing scalable batch and streaming pipelines using Dataflow (Apache Beam) and/or Spark (Dataproc)
• Strong proficiency in BigQuery SQL, including query optimization, partitioning, clustering, and cost control.
• Hands-on experience with Hadoop MapReduce and ecosystem tools (Hive, Pig, Sqoop)
• Advanced Python programming skills for data engineering, including testing and maintainable code design
• Experience managing schema evolution while minimizing downstream impact

Analytics & Data Serving

• Expertise in BigQuery performance optimization and data serving patterns
• Experience building semantic layers and governed metrics for consistent analytics
• Familiarity with BI integration, access controls, and dashboard standards
• Understanding of data exposure patterns via views, APIs, or curated datasets

Data Governance, Quality & Metadata

• Experience implementing data catalogs, metadata management, and ownership models
• Understanding of data lineage for auditability and troubleshooting
• Strong focus on data quality frameworks, including validation, freshness checks, and alerting
• Experience defining and enforcing data contracts, schemas, and SLAs
• Familiarity with audit logging and compliance readiness
• Strong hands-on experience with Google Cloud Platform (GCP), including project setup, environment separation, billing, quotas, and cost controls
• Expertise in IAM and security best practices, including least-privilege access, service accounts, and role-based access
• Solid understanding of VPC networking, private access patterns, and secure service connectivity
• Experience with encryption and key management (KMS, CMEK) and security auditing

DevOps, Platform & Reliability

• Proven ability to build CI/CD pipelines for data and infrastructure workloads
• Experience managing secrets securely using GCP Secret Manager
• Ownership of observability, SLOs, dashboards, alerts, and runbooks
• Proficiency in logging, monitoring, and alerting for data pipelines and platform reliability

Good to have

• Security, Privacy & Compliance

Security, Privacy & Compliance

• Hands-on experience implementing fine-grained access controls for BigQuery and GCS
• Experience with VPC Service Controls and data exfiltration prevention
• Knowledge of PII handling, data masking, tokenization, and audit requirements