Accolite

Senior Data Lake Engineer

Posted On

March 13, 2026

Location

Hyderabad, Telangana

Experience Level

5 - 8 Years Exp.

Job Type

Full Time

Apply By

April 4, 2026

Job Description

Job Title: Data Engineer – AWS Redshift and Data Lake

We are seeking an experienced Data Engineer with strong expertise in building scalable data platforms on AWS. The ideal candidate will design, develop, and optimize large-scale data pipelines, manage enterprise data lakes, and deliver high‑quality data models for analytics and reporting. This role requires hands-on experience with AWS services, Redshift, and modern data engineering frameworks.

Key Responsibilities

Data Engineering & Pipeline Development

Design, build, and maintain ETL/ELT data pipelines using AWS-native tools (Glue, Lambda, Step Functions, EMR).
Develop scalable data ingestion solutions from structured and unstructured sources.
Build data transformation workflows using PySpark, Spark, or SQL-based frameworks.
Ensure data quality, validation, lineage, and governance throughout the lifecycle.

AWS Data Lake & Cloud Architecture

Design and manage large-scale AWS S3-based Data Lakes.
Implement efficient data partitioning, cataloging, and metadata management using AWS Glue Data Catalog.
Optimize storage formats (Parquet/ORC/Delta) for performance and cost efficiency.
Work with architects to define cloud-based data platform standards.

Amazon Redshift Development

Design and optimize Redshift data models, schemas, and distribution/sort keys.
Build high-performance ELT workloads into Redshift using SQL, Spectrum, and COPY commands.
Improve query performance, concurrency, and cluster resource utilization.
Implement workload management (WLM) and monitoring for Redshift clusters.

Data Integration & Enterprise Connectivity

Integrate data from enterprise systems such as CRM, ERP, and third‑party APIs.
Support real-time or near-real-time ingestion using Kinesis, Kafka, or streaming architectures.
Ensure robust and reliable data synchronization across systems and platforms.

Collaboration & Delivery

Partner with data architects, analysts, and business stakeholders to meet data needs.
Participate in solution design discussions and propose scalable data engineering solutions.
Ensure reliability, performance, and security of data pipelines and platforms.

Required Skills

5–7 years of hands-on experience in data engineering.
S3, Glue, Redshift, Lambda, IAM, CloudWatch, EMR.
Deep knowledge of Amazon Redshift including optimization and performance tuning.
Strong SQL skills and experience with data modeling (star/snowflake).
Experience building and managing data lakes and large-scale data pipelines.
Hands-on experience with PySpark/Spark or similar distributed processing frameworks.
Experience with streaming technologies such as Kinesis or Kafka.
Strong understanding of ETL/ELT architecture and data integration patterns.

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