Senior Data Engineer

MACHINE LEARNING TECHNOLOGIES LLC; Atlanta (GA); On-site; USD 90,000 - 117,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC in Atlanta, GA is seeking a Senior Data Engineer to design and optimize production-grade PySpark pipelines and Snowflake data models.

You will work with streaming/batch processing, Iceberg tables, Cortex AI components, and AWS services to deliver scalable data products while balancing cost, performance, and reliability.

Strong collaboration with architects and business teams is essential to deliver secure, maintainable solutions.

Qualifications

• 6+ years of enterprise data engineering experience.
• Strong hands-on PySpark, Spark SQL, Python and advanced SQL.
• Experience reading large S3 Parquet/Delta datasets and deduplication.
• Snowflake expertise with data modeling, SnowSQL, Snowpipe, Streams, Tasks, RBAC and performance tuning.

Responsibilities

• Design production-grade PySpark batch/streaming pipelines; read S3 Parquet/Delta datasets, implement complex transformations and high-volume deduplication.
• Tune Spark with partitioning, caching, broadcast joins and optimization; balance speed, reliability and cost.
• Engineer Snowflake warehouses, schemas and models; implement SnowSQL, Snowpipe, Streams, Tasks, Dynamic Tables and Materialized Views.
• Create Snowflake-managed or externally managed Iceberg tables; implement incremental ingestion and CDC patterns.
• Optimize Snowflake with profiling, clustering and caching; ensure cost efficiency.
• Build Snowpark Python DataFrame transformations, UDFs and stored procedures; evaluate Snowpark Container Services.

Skills

PySpark

Spark SQL

Python

Advanced SQL

Data engineering

Batch/Streaming

Tools

Snowflake

SnowSQL

Snowpipe

Snowpark

Apache Iceberg

Redshift

S3

Glue

EMR

Lambda

Airflow

Databricks

Kinesis

Job description

Job Description

• Job ID: J54825


• Job Title: Senior Data Engineer


• Location: Atlanta, GA


• Duration: 8 Months + Extension


• Domain Exposure: Utilities/ Energy


• Client: To Be Discussed Later


• Employment Type: W-2, 1099, C2C


• Work Authorization: US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other


• Bill Rate: $73/hour (C2C)

Job Description

• Design production-grade PySpark batch/streaming pipelines; read S3 Parquet/Delta datasets, implement complex transformations and high-volume deduplication.


• Tune Spark using partitioning, caching, broadcast joins, shuffle/skew optimization and execution-plan analysis; balance speed, reliability and cloud cost.


• Engineer Snowflake warehouses, schemas and models; implement SnowSQL, Snowpipe, Snowpipe Streaming, Streams, Tasks, Dynamic Tables and Materialized Views.


• Create Snowflake-managed or externally managed Apache Iceberg tables for interoperable lakehouse solutions; implement incremental ingestion and CDC patterns.


• Optimize Snowflake with query profiling, clustering, micro-partition pruning, warehouse sizing, caching and materialization strategies.


• Build Snowpark Python DataFrame transformations, UDFs and stored procedures; evaluate Snowpark Container Services for advanced processing.


• Enable Snowflake Cortex Analyst (semantic models/views, natural-language-to-SQL), Cortex Search (semantic retrieval/RAG) and Cortex AI Functions (summarization, classification, extraction).


• Explore Cortex Agents, Snowflake Intelligence and Snowflake Copilot; integrate LLM workflows, embeddings, APIs, prompt evaluation and governed AI access as appropriate.


• Build AWS-native solutions using S3, Glue, EMR, Lambda, Step Functions and Redshift; manage IAM, CloudWatch, orchestration and operational monitoring.


• Modernize DataStage/Informatica ETL; ensure data quality, validation, reconciliation, lineage, security, audit readiness and complete technical/runbook documentation.


• Collaborate with architects, analysts, TPMs and business teams to deliver maintainable, secure and cost-effective data products.

Required Qualifications

• 6+ years of enterprise data engineering; strong hands‑on PySpark, Spark SQL, Python and advanced SQL (CTEs, window functions, joins, subqueries, tuning).


• Production experience reading large S3 Parquet/Delta datasets, implementing deduplication, and optimizing high-volume PySpark processing.


• Deep Snowflake experience: data modeling, SnowSQL, Snowpipe, Streams, Tasks, RBAC, Iceberg Tables, Dynamic Tables, Materialized Views and performance/cost tuning.


• Working exposure to Snowflake Cortex AI (Cortex Analyst, Search or AI Functions), semantic analytics and Snowpark Python; understanding of GenAI, LLMs, embeddings and RAG.


• Hands‑on AWS S3, Glue, EMR, Lambda, IAM, Step Functions, CloudWatch and Redshift; Airflow, Step Functions or comparable orchestration.


• Knowledge of data warehousing, ETL/ELT, data lakes and lakehouse patterns; strong communication, problem-solving and stakeholder collaboration.

Preferred Qualifications

• Hands‑on Cortex Analyst semantic models/views, Cortex Search/RAG, Cortex Agents, Snowflake Intelligence, Copilot, Snowpark Container Services, Streamlit in Snowflake or Native Apps.


• IBM DataStage/Informatica modernization; Git, Jenkins, GitHub Actions, Terraform and CI/CD; Great Expectations/dbt tests; Kafka/Kinesis; Databricks; Control-M and shell scripting.


• Financial services, regulated mortgage or Fannie Mae/Freddie Mac/GSE programs; Sn

Equal Opportunity Employer

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.